www.thelancet.com/infection Vol 13 April 2013
Tuberculosis 2013: 2
Tuberculosis biomarkers discovery: developments, needs,
Robert S Wallis, Peter Kim, Stewart Cole, Debra Hanna, Bruno B Andrade, Markus Maeurer, Marco Schito, Alimuddin Zumla
Biomarkers are indispensable to the development of new tuberculosis therapeutics and vaccines. The most robust
biomarkers measure factors that are essential to the underlying pathological process of the disease being treated, and
thus can capture the full eff ects of many types of interventions on clinical outcomes in multiple prospective,
randomised clinical trials. Many Mycobacterium tuberculosis and human biomarkers have been studied over the past
decade. Present research focuses on three areas: biomarkers predicting treatment effi cacy and cure of active
tuberculosis, the reactivation of latent tuberculosis infection, and the induction of protective immune responses by
vaccination. Many older, non-specifi c markers of infl ammation, when considered in isolation, do not have suffi cient
predictive values for clinical use in tuberculosis. Although no new accurate, tuberculosis-specifi c biomarkers have yet
been discovered, substantial progress has been made in some areas. However, the qualifi cation of biomarkers as a
surrogate for a clinical endpoint in tuberculosis is very challenging, and, for biomarkers that are non-culture-based,
impossible to pursue without the availability of well characterised biobanks containing biospecimens from patients
who have had adequate follow-up to establish long-term treatment outcome. We review progress in tuberculosis
biomarker development and eff orts being made to harness resources to meet future challenges.
Over the past 5 years, increased donor, governmental,
and corporate investment for the diagnosis,
treatment, prevention, and control of tuberculosis
have led to substantial advancement in the develop-
ment of new diagnostics, drugs, and vaccines.1,2
Accelerated drug development is leading to a new
portfolio of promising drugs against tuberculosis
and regimens for drug-susceptible and drug-resistant
disease, some of which are now under evaluation;
however, discovery of tuberculosis biomarkers has
lagged behind. Over the past decade both human
and Mycobacterium tuberculosis biomarker studies
have focused on three specifi c areas of research:
biomarkers predicting treatment effi cacy and cure of
active tuberculosis, the reactivation of latent tuber-
culosis infection, and the induction of protective
immune responses by vaccination. The non-specifi c
markers of infl ammation such as C-reactive protein,
when considered in isolation, do not have suffi cient
predictive values for clinical use.
Biomarkers are objective characteristics that indicate a
normal or pathogenic biological process, or a pharma-
cological response to a therapeutic intervention or
vaccination.3 Thus they can provide information about
disease status, risk of progression, likelihood of response
to treatment or of drug toxicity, and protective immunity
after vaccination (panel 1). Biomarkers can be the basis
for surrogate endpoints in a clinical trial, replacing
typical clinical endpoints that describe how a patient
feels, functions, or survives. The biomarker-endpoint
association can be shown by trials of antiretroviral
therapy in which a biomarker (plasma HIV RNA) forms
the basis of a surrogate endpoint (eg, the proportion of
patients with undetectable plasma HIV RNA by week 48).
The value of such an endpoint lies in its use for the
prediction of clinically
opportunistic infection or mortality) in short trials with
few patients, thus accelerating clinical research.
The most robust biomarkers measure factors that are
essential to the underlying pathological process of the
disease being treated, and thus can capture the full eff ects
of many types of interventions on clinical outcomes in
multiple prospective, randomised clinical trials. This
meaningful events (eg,
Lancet Infect Dis 2013;
March 24, 2013
This is the second in a Series of
six papers about tuberculosis
Specialty Care, Pfi zer, Groton, CT,
USA (Prof R S Wallis MD),
Departments of Medicine, Case
Western Reserve University,
Cleveland, OH, USA (R S Wallis);
University of Medicine and
Dentistry of New Jersey,
Newark, NJ, USA (R S Wallis);
Division of AIDS (P Kim MD), and
Laboratory of Parasitic Diseases
(B B Andrade MD), National
Institute of Allergy and
Infectious Diseases, National
Institutes of Health, Bethesda,
MD, USA; Global Health
Institute, Ecole Polytechnique
Fédérale de Lausanne, Lausanne,
Switzerland (Prof S Cole FRS);
Critical Path Institute, Salt Lake
City, UT, USA (D Hanna PhD);
Division of Therapeutic
Immunology, LabMed and MTC,
Karolinska Institute and CAST,
Karolinska Hospital, Stockholm,
Sweden (Prof M Maeurer FRCP);
Henry M Jackson Foundation-
Division of AIDS, National
Institute of Allergy and
Infectious Diseases, National
Institutes of Health, Bethesda,
MD, USA (M Schito PhD); Centre
for Clinical Microbiology,
Division of Infection and
Immunity, University College
London, London, UK
(Prof A Zumla FRCP); and
University of Zambia– University
College London Medical School
(UNZA-UCLMS) Research and
Training Programme, University
Teaching Hospital, Lusaka,
Zambia (A Zumla)
Prof Alimuddin Zumla,
Department of Infection,
Centre for Clinical Microbiology,
University College London,
Royal Free Hospital, Rowland Hill
Street, London NW3 2PF, UK
• Many Mycobacterium tuberculosis and human biomarkers
have been studied over the past decade; current research
is focused on three areas: the cure of active tuberculosis,
the reactivation of latent tuberculosis infection, and the
induction of protective immune responses by
• Although no new accurate, tuberculosis-specifi c
biomarkers have yet been discovered, substantial progress
has been made in some areas
• The qualifi cation of biomarkers as a surrogate for a clinical
endpoint in tuberculosis remains very challenging
• The validation of a putative surrogate endpoint in
tuberculosis remains extremely challenging, and for
biomarkers that are non-culture based, requires the
establishment of well characterised biobanks with
biospecimens from patients who have had adequate
follow-up to quantify recurrent disease
• Accelerated tuberculosis biomarker research and
development is anticipated with several funding agencies
increasing investment into tuberculosis biomarker research
www.thelancet.com/infection Vol 13 April 2013 363
proposed highest level of certainty is indicated for month 2
sputum culture status and interferon γ release (table).
Prediction of outcomes in natural history (non-
interventional) studies confers an intermediate level of
certainty. The simple detection of a treatment eff ect not
yet related to a clinical outcome has the lowest level of
certainty, because it depends solely on biological
plausibility for its interpretation. Biomarkers inevitably
overlap with diagnostics, which, by contrast, inform
present rather than future health status. Some
biomarkers can have a dual role (eg, plasma HIV RNA,
which can be used to both diagnose HIV-1 infection and
monitor its treatment), whereas others cannot (eg, HIV
antibody). In some situations, markers that have
confi rmed prognostic value when used to assess disease
extent before treatment initiation can nonetheless fail as
surrogate endpoints when used after treatment has
started; they therefore cannot capture the eff ects of
treatment. One such situation is quantitative detection of
M tuberculosis DNA in sputum, which correlates with
bacterial burden at the time of tuberculosis diagnosis,
but, like the acid fast smear, cannot distinguish live from
dead bacteria as treatment progresses.68
Several candidate biomarkers
M tuberculosis or human infl ammatory immune
responses have been studied over the past decade (table),
describing the reactivation of latent tuberculosis
infection, its durable eradication (relapse-free cure) in
patients with active disease, and the induction of
protective immune responses by vaccination. 69,70 With the
exception of month 2 culture status, the size of these
studies falls far short of research needs. Many older, non-
specifi c markers of infl ammation, when used alone, can
have insuffi cient predictive value for clinical use in
tuberculosis, although a combination of the biomarkers
highlighted in the table has a theoretical potential to help
assessment of clinical cure, or risk of relapse or
reactivation. For example, high levels of neopterin (a
non-specifi c marker of macrophage activation) that
persist despite appropriate tuberculosis treatment are
associated with increased risk of relapse or reactivation,
but only in people without concomitant HIV-1 infection
or other complicating medical conditions.42 Although no
new accurate, tuberculosis-specifi c biomarkers have yet
been discovered, substantial progress has been made in
some areas since this subject was last reviewed in this
journal.71 In this Series paper we discuss this progress.
Prediction of relapse-free tuberculosis cure
The introduction of rifampicin and pyrazinamide nearly
50 years ago transformed tuberculosis treatment,
allowing the necessary duration of treatment to be
shortened from 18 months to 6 months without an
increase in the rate of recurrence due to relapse.
Tuberculosis treatment is poised for a second such
transformation,4 with development underway of several
Panel 1: Predictive roles for tuberculosis biomarkers
Prediction of tuberculosis cure
• Emergence of resistance
• Recurrence due to relapse
• Drug toxicity
Prediction of tuberculosis reactivation
• Progression from primary infection to disease
• Reactivation of latent infection
• Eradication of latent infection
Prediction of protective immunity
• Vaccine effi cacy
• Adjunctive immunotherapy effi cacy
• Recurrence due to reinfection
Month 2 culture statusRequired duration of treatment4
Treatment eff ect6
Extent of disease at start of treatment7,8
Treatment eff ect9–11
Treatment eff ect13–16
Inability to distinguish curative vs non-curative treatment18
Inability to distinguish 6 vs 18 month regimens19
Inability to detect curative eff ect of linezolid20
Treatment eff ect
Correlation with month 2 status21,22
Treatment eff ect23
Treatment failure and relapse16–18
Treatment eff ect24
Treatment eff ect25
Treatment eff ect26
Mycobacterium tuberculosis DNA
(GeneXpert MTB/RIF assay)
M tuberculosis RNA
Liquid culture time to positive in
automated liquid culture
Early bactericidal activity, 7–14 days
Serial colony counts, 1–2 months
Urine tuberculosis DNA
Volatile organic compounds
Interferon γ release assay (ELISPOT
or whole blood)
Latent infection treatment (no eff ect)31,32
Latent infection eff ect33
Subsequent active tuberculosis 35–37
Treatment eff ect38,39
Correlation with month 2 status40
Treatment eff ect41
Treatment eff ect43
Whole blood bactericidal activity
Soluble intercellular adhesion
Soluble tumour necrosis factor
receptor, granzyme B
Sputum interferon γ
Soluble urokinase plasminogen
Treatment eff ect44
Extent of disease at start of treatment45
Treatment eff ect46
Treatment eff ect, death47–49
Correlation with month 2 status51
(Continues on next page)
www.thelancet.com/infection Vol 13 April 2013
promising drugs with entirely novel mechanisms of
action. A report qualifying month 2 sputum culture
status as a biomarker for relapse has helped with early
testing of new regimens containing these compounds.72
However, that analysis, which showed that changes in
treatment that aff ected relapse risk were highly likely to
also aff ect month 2 culture status (p<0∙00001), did not
directly inform the necessary duration of these new
regimens—a potential stumbling block if they are to be
effi ciently made available to patients in greatest need.
No full synthesis has been done for the role of month 2
culture status as a biomarker predictor of required
duration of treatment, although an analysis in which
regimens were classifi ed according to inclusion of
rifampin and pyrazinamide suggested the problem could
be addressed with modelling.4 Researchers investigated
the connection between relapse risk, treatment duration,
and month 2 culture status using meta-regression
analysis (Wallis RS, unpublished). The model built from
this study indicated an upper 80% prediction limit for
relapse of less than 10% for a hypothetical phase 3 trial
with 680 patients per group for a new regimen with a
month 2 culture positive rate of 1%. The fi nding was
proposed to support accelerated regulatory approval
of new regimens for patients with drug-resistant
By contrast with the month 2 endpoint, trials of early
bactericidal activity (EBA) of 1–2 weeks in duration have
repeatedly failed to capture important diff erences in
clinical outcomes between treatment groups in
prospective, randomised controlled trials, because they
cannot distinguish between eff ective versus ineff ective
treatments (rifampicin plus isoniazid vs isoniazid alone)
or regimens requiring 6 months versus 18 months for
cure .18,19 The absence of sustained EBA of linezolid
contrasts starkly with its ability to cure extensively drug-
resistant tuberculosis.20,73 The discrepancy does not seem
to be due to variability in measuring sputum colony
counts, because independent EBA trials of a similar
design have yielded similar results.74 Instead, EBA seems
mainly to measure eff ects of treatment on extracellular
myco bacteria in large lung cavities, which seem to play
only a small part in relapse.
Automated liquid culture systems such as mycobacterial
growth indicator tube are increasingly used worldwide for
tuberculosis diagnosis. These standardised systems are
attractive platforms for
particularly because they routinely report the time interval
needed for detection of growth—a variable that is strongly
inversely correlated with inoculum size when tested with
laboratory stock cultures (Pearson’s correlation coeffi cient
-0∙970; p=0∙006).75 The correlation is reduced but remains
signifi cant when tested with sputum samples obtained
during tuberculosis treatme nt.13–15 This correlation
increases the feasibility of quantitative modelling of
treatment eff ects in large clinical trials. Research suggests
that the most informative time for this modelling will be
during the second month of treatment.19 Questions
remain about the optimum methods for specimen
collection (pooled over 12–16 h vs spot) and processing
(decon tamination with sodium hydroxide variably
decreases mycobacterial viability).
Other culture-based methods have been described
with resuscitation-promoting factors to help with the
detection of otherwise non-culturable mycobacteria that
become more frequent in sputum as treatment
progres ses—eg, Mukamolova and colleagues76 used
resuscitation-promoting factors in a preliminary study.
The prognostic signifi cance of such cultures is unknown.
Further studies of the ability to resuscitate or recognise
live but dormant non-replicating bacilli, and mechanisms
behind relapse, could lead to improvements in existing
culture-based detection systems, making them more
powerful as possible intermediate endpoints in
tuberculosis drug trials.
Molecular alternatives to culture
PCR-based methods for quantitation of viable mycobacteria
are feasible. The GeneXpert MTB/RIF assay (Cepheid,
Sunnyvale, CA, USA) was developed as an automated,
highly sensitive, and rapid molecular diagnostic for
pulmonary tuberculosis.77,78 PCR amplifi cation with real-
time detection using molecular beacon probes to detect
M tuberculosis DNA is used in the assay. As such, the assay
amplifi es DNA from both live and dead bacteria in clinical
sputum samples. The test indirectly gives quantitative
measures of M tuberculosis DNA as cycle thresholds of
PCR amplifi cation, showing a high degree of accuracy and
reproducibility in serially diluted laboratory specimens
(Continued from prevous page)
Natural killer T cells
Mycobacterial growth inhibition
Extent of disease at start of treatment28
Vaccine eff ect52,53
Revaccination (no eff ect)54
Correlation with other markers52,53,55–59
Subsequent active tuberculosis60
Subsequent active tuberculosis60
Subsequent active tuberculosis60
Subsequent active tuberculosis35,61
Diagnosis of subclinical tuberculosis36
Diagnosis of active tuberculosis vs latent infection62,63
Treatment eff ect62,87
Diagnosis of active tuberculosis vs other chronic
infl ammatory diseases65
Diagnosis of active tuberculosis vs latent disease66
Diagnosis of active tuberculosis vs latent disease67
Natural killer and CD4 T cells
Whole blood interferon γ release
ELISPOT=enzyme-linked immunosorbent spot assay. *Data do not support a role as biomarker. †III=high certainty,
capturing differences in clinical outcomes across treatment groups in prospective randomised trials; II=intermediate
certainty, predicting differences in outcomes in patients in non-interventional studies; and I=low certainty, biological
plausibility without association with clinical outcome.
Table: Candidate biomarkers in tuberculosis
www.thelancet.com/infection Vol 13 April 2013 365
and pretreatment sputum sam ples.7 Studies are in
progress to establish whether viable and non-viable
M tuberculosis bacilli can be distinguished by pretreatment
with propidium monoazide, which enters damaged
mycobacteria, covalently binding DNA after light exposure,
and thus preventing DNA amplifi cation.6 Other, manual
methods to measure viable mycobacteria in sputum based
on amplifi cation of RNA have been described that generally
correlate well with colony-forming unit counts during
Lipoarabinomannan is a major constituent of the
mycobacterial cell wall that can be detected in a patient’s
urine by commercial ELISA. Although the sensitivity of
this assay is adequate for tuberculosis diagnosis only in
patients with far-advanced HIV infection, its performance
might be improved by combination with DNA detection
or by modifi cation of test var iables.79,80 Results of a study
by Wood and colleagues 25 showed that concentrations of
lipoarabinomannan decreased slowly, after 1–2 months
of combined tuberculosis and HIV treatment, in a small
set of patients with positive urine lipoarabinomannan
results at start of treatment. Further studies of
lipoarabinomannan as a candidate biomarker might be
of interest, especially since new assays with lower
detection thresholds could make the approach more
widely ap plicable.81 Ethambutol acts by blocking
lipoarabinomannan synthesis,82 and so more studies will
be needed to establish whether its eff ects are
overestimated by the monitoring of lipoarabinomannan.
Imaging of lung lesions during treatment by combined
PET and CT can infl uence early tuberculosis drug and
regimen development and increase the accuracy of
predictions of relapse in individual patients. Combined
imaging allows the superposition of two types of data:
structural data from CT (which diff erentiate lesions
according to x-ray densities), and functional data from
PET (which, when undertaken with 18fl uorodeoxyglucose
[¹⁸F-FDG], detect metabolic activity of mammalian
infl ammatory cells). Studies in the rabbit tuberculosis
model show distinct types of lesions with diff erent
natural histories and diff erent early responses to
che motherapy.83 ¹⁸F-FDG intensity reaches a maximum
in the rabbit model 5 weeks after infection, but stabilises
or decreases during the next month as the infection
reaches a chronic stage. Individual lesions in the same
animal have very diff erent fates at this stage, ranging
from complete resolution to striking progression.
Chemotherapy with either isoniazid or rifampicin
reduces ¹⁸F-FDG uptake and, more slowly, CT lesion
density and volume. Findings from one study showed
reduced ¹⁸F-FDG uptake after 1 month of tuberculosis
treatment in 19 of 2 1 patients.23 Of the two PET non-
responders, one had delayed sputum culture conversion
(still positive at 3 months), and the other was later
shown to have lymphoma. Clinical studies are underway
to examine the link between changes in PET and CT
scans and clinical outcomes during tuberculosis
treatment. Despite the high costs associated with this
approach, it could be an indicator of drug activity and an
aid to dose and regimen selection in early drug trials,
and a predictor of relapse risk at the end of treatment in
Gene expression profi les
Changes in tuberculosis-specifi c gene and protein
expression profi les (transcriptomics) could be of value in
assessment of the early response to tuberculosi s
treatment.84–86 A study by Berry and colleagues62 showed
that a multitranscript interferon-driven neutrophil
signature diff erentiated patients with tuberculosis from
controls, correlated with radiographic extent of disease,
and diminished in seven patients after 2 months of
ultimately successful tuberculos is treatment. A similar
study assessed interferon-driven signatures earlier
during treatment in 29 patients.87 Changes in gene
expression levels were readily detectable after 2 weeks of
treatment (fi gure).
A study of 27 patients with pulmonary tuberculosis
assayed at diagnosis and during treatment showed
signifi cant changes in expression of more than 4000 genes
in blood during treatment.88 Rapid, large-scale changes
were detected, with downregulated expression of
1261 genes within the fi rst week, including infl ammatory
markers such as complement components C1q and C2.
Subsequent changes include B-cell signalling pathways.
These results indicate the possibility that measurement
of host factors such as gene expression profi les during
the fi rst few weeks of treatment could be suitable for
biomarkers of treatment effi cacy and would have benefi ts
for early-phase and mid-phase clinical trials, providing
more information about clinical outcome than would
quantitative sputum microbiology. Further studies are
warranted to assess the prognostic signifi cance of these
signatures for tuberculosis reactivation and cure.
Prediction of reactivation of latent infection
Interferon γ release
In most instances, infection with M tuberculosis is
contained by the host immune response, preventing the
progression to active disease. Tests for latent tuberculosis
infection such as the tuberculin skin test and tuberculosis
antigen-stimulated interferon γ release assay detect
sensitisation to mycobacterial antigens, but do not
diff erentiate between persistent and resolved latent
infection. For example, two studies of latent infection
treatment with isoniazid did not show a consistent eff ect
on early secretory antigenic target-6 and culture fi ltrate
protein-10-induced interferon γ responses with whole
blood culture or enzyme-linked immunoa bsorbent
spot.31,32 As a result, interferon γ release assays cannot
www.thelancet.com/infection Vol 13 April 2013
specifi cally identify those with highest risk o f
reactivation.89,90 In one meta-analysis, the predictive value
of a positive interferon γ release assay for subsequent
progression to active tuberculosis increased to 8–15% if
testing was not restricted to individuals with a positive
tuber culin skin test.91 Findings from some studies have
shown substantial increases in interferon γ release
shortly before the diagnosis of act ive tuberculosis,35–37
suggesting that a higher threshold for positivity might
improve its predictive value, at least in people who are
not overtly immunocompromised.
The largest prospective study of individuals at high
tuberculosis risk (defi ned as recent household contacts
of active tuberculosis cases) who were not overtly
immunocompromised identifi ed only 26 incident
tuberculosis cases in 2348 contacts over 4312 person-
y ears of follow-up.60 Most cases occurred within the fi rst
year after study entry. Samples of plasma and viable cells
were available for analysis to identify predictors of
disease progression in more than half of these cases.
Increased concentrations of interleukin 18, a marker of
innate immune activation, diff erentiated those who
developed tuberculosis from controls, as did signifi cantly
higher expression of chemokine (c-c motif) receptor
(CCR7) and lower expression of Bcl2 in RNA extracted
from blood. Interleukin 18 concentrations are increased
in patients with active tuberculosis, in proportion to
radiographic extent of disease.92 In tuberculosis and
other chronic infl ammatory diseases, interleukin 18
supports T-cell activation and interferon γ production.
CC chemokines have an important role in the homing of
lymphocytes to sites of infl ammation, and are likely to
be involved in the early responses to M tuberculosis
infection. These fi ndings support the notion that latent
infection reactivation might, at least in some cases, be a
relatively slow, gradual process, in which measurable
changes in the immune system precede the development
of active disease by a long interval. The signifi cance of
reduced expression of Bcl2, an inhibitor of apoptosis, is
uncertain, since antigen-driven T-cell apoptosis is
increased in tuberculosis, both in blood and at the site of
infection.64,93 Diff erential Bcl2 expression in monocytes
and T cells might account for the contrary fi ndings at
gene and cellular levels.
These fi ndings emphasise the importance of innate
immunity in defences against tuberculosis and identify a
set of biomarkers indicating potential tuberculosis risk.
The fi ndings also show the logistical challenges faced in
the conduct of prospective, longitudinal studies of the
natural history of M tuberculosis infection. Most such
studies have been hampered by identifi cation of relatively
more coprevalent cases than incident cases, even in high-
risk individuals in tuberculosis households. Such
coprevalent cases, sometimes termed subclinical
tuberculosis, are uncovered by careful history, chest
radiography, and sputum culture using liquid medium;
patients generally have reduced symptoms and limited
extent of disease compared with index cases.94 Subclinical
cases occur in patients both w ith and without HIV.94–97
The extent to which these cases represent a stable disease
phenotype is uncertain, particularly in people with HIV
with low CD4 T-cell counts. Data from the pre-
chemotherapy era in the USA indicate a distinct natural
history in tuberculosis cases with minimal radiographic
extent of disease, with two-thirds of individuals showing
apparent spontaneous resolution of the illness (so-called
Figure: Changes in gene expression profi les during early tuberculosis treatment
(A) Profi le plot of all detectable transcripts (15 837), obtained without any fi ltering, in the treated patients with active tuberculosis in the South Africa 2011 cohort. Gene expression changes after only
2 weeks of treatment. Normalised expression at 0 months. (B) Temporal molecular response showing the quantitative response to antituberculosis treatment in a 664-gene transcript using linear mixed
models (dots represent mean and bars show 95% CI). Reproduced from Bloom and colleagues,87 by permission of PLoS One.
Temporal molecular response
Normalised intensity values
www.thelancet.com/infection Vol 13 April 2013 367
arrested tuberculosis) within 3 years.98 Nonetheless,
using this population is an attractive alternative for
researchers exploring the identifi cation of early bio-
markers of tuberculosis risk, because these patients
represent an intermediate stage between the two
traditional categories of latent and active infection that is
amenable to study by host signatures. The study of
subclinical cases to inform early tuberculosis reactivation
is further supported by serological studies indicating
diff erential recognition of stage-specifi c mycobacterial
antigens in subclinical cases.99–102
MicroRNA and metabolomic profi les
Patient classifi cation by gene expression or other profi les
is inevitably imperfect. For example, the study by Berry
and colleagues62 of transcriptional tuberculosis signatures
misclassifi ed about 10% each of cases and controls. The
misclassifi ed tuberculosis cases had minimally abnormal
chest radiographs and minimally abnormal gene
expression profi les. A reasonable question would be
whether the misclassifi ed controls represent early events
in the process of reactivation of latent infection. A study
of microRNA profi les in 29 patients with tuberculosis,
29 people with latent infection, and 18 controls identifi ed
17 micro-RNAs that were diff erentially expressed among
the groups.67 Two individuals with latent infection
showed profi les similar to those with tuberculosis.
Similarly, Weiner III and colleagues66 explored the
metabolomic profi les of more than 400 small molecules
in serum of 46 people with latent infection with no
clinical signs of tuberculosis and 44 patients with clinical
signs of pulmonary tuberculosis. The investigators noted
increased activity of indoleamine 2,3-dioxygenase 1,
decreased phospholipase activity, increased abundance
of adenosine metabolism products, and indicators of
fi brotic lesions in patients with active disease compared
with those with latent infection. They recorded that
20 metabolites were suffi cient for robust but imperfect
discrimination of patients with tuberculosis from healthy
individuals. Furthermore, researchers have found that
systemic concentrations of haemeoxygenase-1 (HO-1)
were increased in individuals with active pulmonary and
extrapulmonary tuberculosis (BB Andrade, unpublished).
HO-1 concentrations eff ectively dis criminated active
from latent tuberculosis and there was a marked
reduction in HO-1 levels in active tuberculosis cases after
antituberculous therapy, but not in those for whom
treatment was unsuccessful.
The misclassifi ed latent infection cases in these series
could simply be due to test error, but they could represent
early events in the reactivation process. Findings from
further cross-sectional studies of these markers in people
with latent infection, subclinical tuberculosis, and overt
active disease will help to assess their potential value in
prediction of both tuberculosis cure and reactivation;
prospective longitudinal trials will ultimately be needed
for their qualifi cation.
Prediction of protective immunity induction by
Much data have been published on the role of CD8+ and
CD4+ adaptive T-cell responses directed against
M tuberculosis.103 Advances in response analyses showed
that immune responses in infections are impaired and
T cells express specifi c exhaustion markers, including
PD-1 (programmed cell death protein 1) or TIM-3 (T-cell
immunoglobulin and mucin
molecule 3).104 By contrast with the generally accepted
model, TIM-3+ T cells show stronger immune eff ector
functions, defi ned by Th1 and Th22 cytokine prod-
uction, cytotoxic T-lymphocyte function, and reduced
M tuberculosis repl ication in macrophages.105 Decreased
cellular immune responses in patients with tuberculosis
have also been associated with altered SOCS3 (suppressor
of cytokine signalling 3) expression. SOCS3 regulates
cytokine signalling and aff ects T-cell polarisation. SOCS3
is increased in M tuberculosis-specifi c T cells; it could
therefore represent an exhaustion biomarker,106 or
enhance expansion of interleukin-17-producing immune
cells, or both.107 Perhaps the most surprising fi nding was
identifi cation of the antimicrobial activity of mucosal-
associated invariant T cells. In individuals without active
disease they express as the invariant TCRα (T cell
receptor α) chain VA7.2-Ja33, are restricted by the MR1
(MHC class 1 related) antigen, can display M tuberculosis-
spec ifi c eff ector functions,108 and are enriched in the lung
(compared with the peripheral circulation in patients
w ith active tuberculosis).109
16 new tuberculosis vaccine candidates have been
clinically trialled in the past decade.110 In most instances,
their development has proceeded by evaluation of
protective effi cacy in an animal model, and then
assessment of immunogenicity in people by measure-
ment of T-cell frequencies and cytokine profi les.
However, studies showing the poor correlation of these
measures (including polyfunctional T-cell responses)
with protection against tubercul osis after BCG
vaccination111 have focused attention on the need for
other indicators of vaccine-induced protection.
Bactericidal or viral neutralisation assays have eased
development of all other licensed vaccines. Several such
assays have been described for M tuberculosis with
mononuclear c ell or whole blood culture.52,55,112,113
Immune control of growth in these assays is inferior in
people who are tuberculin-skin-test-negative and in
young children enhanced by BCG vaccination or
vitamin D; impaired by chemokine receptor blockade,
T-cell depletions, or HIV infection; and restore d by
antiretroviral therapy.52,53,55–59,113–16 These fi ndings indicate
their plausibility as correlates of protection. Fletcher
and col leagues54 examined the ability of whole blood and
mononuclear cell growth inhibition assays to detect
eff ects of BCG vaccination in 30 British adults with or
without a previous history of BCG vaccination. They
used time to detection in mycobacterial growth indicator
www.thelancet.com/infection Vol 13 April 2013
tube rather than colony-forming unit counting to assess
mycobacterial viability in assays. Volunteers were
followed up for 6 months to assess the reproducibility of
growth inhibition and to examine the evolution of
responses over time. A single BCG vaccination is
protective in this population, particularly against severe
forms of tuberculosis,117 whereas repeated vaccination is
not.118–122 The study results showed that both assays were
suffi ciently reproducible, and investigators noted
incremental vaccine-induced growth inhibition only in
patients without a previous history of BCG vaccination.
Furthermore, although T-cell frequencies increased
after vaccination, they did not correlate with growth
inhibitory activity. Further studies of these assays after
vaccination in people in tuberculosis-endemic regions
are warranted to assess the potential correlation with
Future of tuberculosis biomarker research
Whereas several possible biomarkers of treatment
response, cure, and relapse have been proposed from
small, geographically restricted patient cohorts, none
has been validated, largely due to unavailability of well
characterised biobanks for biomarker research. What
is required are central biobanks (collections of bio-
specimens—eg, cells, tissue, blood, serum, sputa,
DNA—with associated clinical and laboratory data and
information from large cohorts of patients who have
had adequate follow-up through to cure, relapse, or
recurrent disease). Availability of these biobanks will
allow a com prehensive set of analyses to be done using
routine and advanced techniques. This will enable
better under standing of tuberculosis pathogenesis
(panel 2) and identifi cation and evaluation of new
biomarkers. Thus, the main barrier to the development
of biomarkers into validated surrogates of treatment
response has historically been insuffi cient funding
rather than scientifi c knowledge. Further funder
investments into research that overcome barriers to the
development of novel tuberculosis biomarkers and to
building biobanks for providing well characterised
samples for the validation of these biomarkers are
needed.123 Several funding agencies have increased
investment into biomarker studies, including the US
National Institutes of Allergy and Infectious Diseases
(NIAID), US Food and Drug Administration (FDA),
British Medical Research Council, European Developing
Countries Clinical Trials Partnership, and Bill & Melinda
Gates Foundation. Ten new projects funded by the Gates
Foundation include several new areas of research, such
as studies of M tuberculosis small RNAs,124 disease-
specifi c cytokine profi les,125–127
mycobacterial constituents released by exosomes of
cells in infected tissues.128 The NIAID has also published
an initiative to expand fundamental understanding of
latent tuberculosis infection, especially in the setting of
An optimum setting in which putative surrogates of
treatment response could be eff ectively assessed is
within clinical drug trials or in non-interventional
observational cohorts in which participants are well
characterised and followed in a rigorous and
standardised way. Cross-sectional studies of close
tuberculosis contacts without HIV with minimally
important information about candidate biomarkers, and
inform the biological basis and stability of this
phenotype. Ideally, such prospective studies, inter-
ventional or not, would have the following components:
detailed clinical, radiographical, and micro biological
treatment dosing; culture confi rmation of tuberculosis
at baseline and all treatment and follow-up timepoints;
and, most importantly, systematic follow-up of study
participants for at least 6–12 months after treatment
randomisation or assignment to investigational or
standard-of-care antituberculosis regimens allowing
comparisons of two therapies with diff erent effi cacies,
and as such are ideally suited to establishment of
surrogate capabilities of a biomarker.
As investment and activity in biomarker research
increases, rapid communication of crucial fi ndings and
coordination of broad research activities are essential to
avoid duplication of eff orts, maximise resources, and
accelerate the translation of basic discovery to clinical
applications. Eff orts are underway to establish collaborative
and harmonised prospective cohort studies in several
high-prevalence countries. Proper cooperation and
collaboration will allow the creation of an international
and analysis of
disease could provide
strict observation of
clinical trials provide
Panel 2: Priorities for biomarker research
• Increase research funding for accelerating biomarker
• Maximise and optimise biomarker research through
coordination and increased collaborations between basic
(fundamental) scientists, clinical triallists, pharmaceutical
industry, and end users
• Establish central biobanks of well characterised
biospecimens from well defi ned patient and contact cohorts
with long-term follow-up
• Delineate the specifi c mechanisms of protective immune
networks between people (host) and Mycobacterium
• Identify specifi c single biomarkers or combinations of
biomarkers that can distinguish latent tuberculosis infection
versus subclinical versus active tuberculosis disease; identify
those who are at highest risk for progression to disease;
predict treatment effi cacy and cure; predict reactivation of
tuberculosis; and predict protective immunity
• Validate new biomarker discoveries and translate new
biomarker discoveries into functional point-of-care use
www.thelancet.com/infection Vol 13 April 2013 369
network of coordinated prospective cohorts that can not
only facilitate biomarker discovery, but also allow the
validation of candidate markers between diff erent
epidemiological settings and populations with samples
and data collected in a standardised way. Any analytical
technique used to measure a biomarker will probably need
adaptation for routine clinical use, because the biomarker
might prove to be useful for both clinical trials and clinical
monitoring. Additionally, as the number of potential
biomarkers grows, understanding the profi le of desired
characteristics (ie, target product profi le) for each of the
three biomarker research areas will be important.
In an eff ort to establish a tuberculosis biobank to be
used in biomarker evaluation, the Global TB Alliance, the
AIDS Clinical Trials Group, and the TB Trials Consortium
have joined together to create the Consortium for TB
Biomarkers (CTB2) whose goal is to collect specimens of
sputum, serum, urine, and other tissue from people with
culture-c onfi rmed pulmonary tuberculosis.128 The project
is led by the TB Alliance and funded by the US FDA and
NIAID. The biobank is the fi rst federally funded biobank
of its type, and is expected to gather a core set of biological
samples from an estimated 1000 patients with culture-
confi rmed pulmonary tuberculosis enrolled in clinical
trials and observational cohort studies done by the three
tuberculosis networks and other partners. Representatives
from participating networks, partners, FDA, and the
NIAID have formed a governing body to determine
procedures and criteria for access to the specimens and
data for biomarker development.
Any analytical technique used to measure the
biomarkers should be adaptable for routine clinical use,
because the biomarker might prove to be useful for both
clinical trials and clinical monitoring. The qualifi cation
of a putative surrogate endpoint in tuberculosis is very
challenging, and, for biomarkers that are non-culture-
based, impossible to pursue without the availability of
well characterised biobanks with bio specimens from
patients who have had adequate follow-up to quantify
recurrent disease. Shortfalls of ongoing biomarker
studies have included: poor defi nitions for active
tuberculosis, latent tuberculosis, and relapse; small
sample numbers in cohorts studied; variations between
study cohorts, and geographical location of study; poor
quality-control of standard laboratory techniques and
platforms, and their reproducibility; and heterogeneous
datasets. We have an opportunity to coordinate the
qualifi cation of new tuberculosis biomarkers with the
confi rmatory phase 3 trials of new tuberculosis drugs;
we should do our utmost to make this eff ort succeed.
RSW and AZ wrote the initial, subsequent, and fi nal drafts. All authors
contributed to the fi nalisation of the article.
Confl icts of interest
RSW is a Pfi zer employee and shareholder. All other authors declare that
they have no confl icts of interest.
We acknowledge support from the European and Developing Countries
Clinical Trials Partnership (EDCTP), Netherlands, EDCTP grants
REMOX PANACEA (AZ), and TB-NEAT (MM, AZ); UK Medical
Research Council (AZ); UBS Optimus Foundation, Switzerland (AZ,
MM); University College London Hospitals (UCLH) Comprehensive
Biomedical Research Centre (AZ); NIH Intramural Research Program
(BBA); and the UCLH National Health Service Foundation Trust (AZ).
1 WHO. Global tuberculosis report 2012. Report number WHO/
HTM/TB/2012.6. Geneva: World Health Organization, 2012. http://
(accessed 5 Dec, 2012).
2 WHO. TB: a global emergency. Report number WF 205 94 TB C.2.
Geneva: World Health Organization, 1994. http://whqlibdoc.who.
int/hq/1994/WHO_TB_94.177.pdf (accessed Sept 22, 2011).
3 Biomarkers working group. Biomarkers and surrogate endpoints:
preferred defi nitions and conceptual framework.
Clin Pharmacol Ther 2001; 69: 89–95.
4 Wallis RS. Sustainable tuberculosis drug development.
Clin Infect Dis 2013; 56: 106–13.
5 Mitchison DA. Assessment of new sterilizing drugs for treating
pulmonary tuberculosis by culture at 2 months [letter].
Am Rev Respir Dis 1993; 147: 1062–63.
6 Miotto P, Bigoni S, Migliori GB, Matteelli A, Cirillo DM. Early
tuberculosis treatment monitoring by Xpert(R) MTB/RIF.
Eur Respir J 2012; 39: 1269–71.
7 Blakemore R, Nabeta P, Davidow AL, et al. A multisite assessment
of the quantitative capabilities of the Xpert MTB/RIF assay.
Am J Respir Crit Care Med 2011; 184: 1076–84.
8 Darban-Sarokhalil D, Imani Fooladi AA, Maleknejad P, et al.
Comparison of smear microscopy, culture, and real-time PCR for
quantitative detection of Mycobacterium tuberculosis in clinical
respiratory specimens. Scand J Infect Dis 2012; published online
Oct 31. DOI:10.3109/00365548.2012.727465.
9 Honeyborne I, McHugh TD, Phillips PP, et al. Molecular bacterial
load assay, a culture-free biomarker for rapid and accurate
quantifi cation of sputum Mycobacterium tuberculosis bacillary load
during treatment. J Clin Microbiol 2011; 49: 3905–11.
10 Li L, Mahan CS, Palaci M, et al. Sputum Mycobacterium tuberculosis
mRNA as a marker of bacteriologic clearance in response to
anti-tuberculosis therapy. J Clin Microbiol 2010; 48: 46–51.
11 Desjardin LE, Perkins M, Wolski K, et al. Measurement of sputum
M tuberculosis messenger RNA as a surrogate for response to
chemotherapy. Am J Respir Crit Care Med 1999; 160: 203–10.
12 Epstein MD, Schluger NW, Davidow AL, Bonk S, Rom WN,
Hanna B. Time to detection of Mycobacterium tuberculosis in sputum
culture correlates with outcome in patients receiving treatment for
pulmonary tuberculosis. Chest 1998; 113: 379–86.
13 Hesseling AC, Walzl G, Enarson DA, et al. Baseline sputum time
to detection predicts month two culture conversion and relapse in
non-HIV-infected patients. Int J Tuberc Lung Dis 2010; 14: 560–70.
14 Bark CM, Okwera A, Joloba ML, et al. Time to detection of
Mycobacterium tuberculosis as an alternative to quantitative cultures.
Tuberculosis (Edinb) 2011; 91: 257–59.
Search strategy and selection criteria
We searched in PubMed and Google Scholar (Jan 1, 1980–Dec 31,
2012), the Cochrane Library (Jan 1, 2001–Dec 31, 2012), and
Embase (Jan 1, 2001–31 Dec, 2012) for English language
publications with the terms “tuberculosis”, “Mycobacterium
tuberculosis” plus “biomarker”, “vaccine”, “gene expression”,
“micro-RNA”, “proteomics”, “metabolomics”, “positron”,
“interferon gamma release”, or “clinical trial”. We also reviewed
studies cited by articles identifi ed by this search strategy and
selected those that we identifi ed as relevant. Some review
articles are cited to provide readers with more details and
references than this review can accommodate.
www.thelancet.com/infection Vol 13 April 2013
15 Weiner M, Prihoda TJ, Burman W, et al. Evaluation of time to
detection of Mycobacterium tuberculosis in broth culture as a
determinant for end points in treatment trials. J Clin Microbiol 2010;
16 Wallis RS, Perkins M, Phillips M, et al. Induction of the antigen
85 complex of M. tuberculosis in sputum: a determinant of outcome
in pulmonary tuberculosis. J Infect Dis 1998; 178: 1115–21.
17 Wallis RS, Perkins M, Phillips M, et al. Predicting the outcome of
therapy for pulmonary tuberculosis. Am J Respir Crit Care Med
2000; 161: 1076–80.
18 Wallis RS, Phillips M, Johnson JL, et al. Inhibition of INH-
induced expression of M. tuberculosis antigen 85 in sputum: a
potential surrogate marker in TB chemotherapy trials.
Antimicrob Agents Chemother 2001; 45: 1302–04.
19 Brindle R, Odhiambo J, Mitchison DA. Serial counts of
Mycobacterium tuberculosis in sputum as surrogate markers of the
sterilising activity of rifampicin and pyrazinamide in treating
pulmonary tuberculosis. BMC Pulm Med 2001; 1: 2.
20 Dietze R, Hadad DJ, Peloquin C, et al. Early and extended early
bactericidal activity of linezolid in pulmonary tuberculosis.
Am J Respir Crit Care Med 2008; 178: 1180–85.
21 Rustomjee R, Diacon AH, Allen J, et al. Early bactericidal activity
and pharmacokinetics of the diarylquinoline TMC 207 in
pulmonary tuberculosis. Antimicrob Agents Chemother 2008;
22 Davies GR, Brindle R, Khoo SH, Aarons LJ. Use of nonlinear
mixed-eff ects analysis for improved precision of early
pharmacodynamic measures in tuberculosis treatment.
Antimicrob Agents Chemother 2006; 50: 3154–56.
23 Martinez V, Castilla-Lievre MA, Guillet-Caruba C, et al. (18)F-FDG
PET/CT in tuberculosis: an early non-invasive marker of
therapeutic response. Int J Tuberc Lung Dis 2012; 16: 1180–85.
24 Goodridge A, Cueva C, Lahiff M, et al. Anti-phospholipid antibody
levels as biomarker for monitoring tuberculosis treatment
response. Tuberculosis (Edinb) 2012; 92: 243–47.
25 Wood R, Racow K, Bekker LG, et al. Lipoarabinomannan in urine
during tuberculosis treatment: association with host and pathogen
factors and mycobacteriuria. BMC Infect Dis 2012; published
online Feb 27. DOI:10.1186/1471-2334-12-47.
26 Cannas A, Goletti D, Girardi E, et al. Mycobacterium tuberculosis
DNA detection in soluble fraction of urine from pulmonary
tuberculosis patients. Int J Tuberc Lung Dis 2008; 12: 146–51.
27 Azzurri A, Kanaujia GV, Sow OY, et al. Serological markers of
pulmonary tuberculosis and of response to anti-tuberculosis
treatment in a patient population in Guinea.
Int J Immunopathol Pharmacol 2006; 19: 199–208.
28 Veenstra H, Baumann R, Carroll NM, et al. Changes in leucocyte
and lymphocyte subsets during tuberculosis treatment;
prominence of CD3dimCD56+ natural killer T cells in fast
treatment responders. Clin Exp Immunol 2006; 145: 252–60.
29 Syhre M, Chambers ST. The scent of Mycobacterium tuberculosis.
Tuberculosis (Edinb) 2008; 88: 317–23.
30 Phillips M, Cataneo RN, Condos R, et al. Volatile biomarkers of
pulmonary tuberculosis in the breath. Tuberculosis (Edinb) 2007;
31 Adetifa IM, Ota MO, Jeff ries DJ, et al. Interferon gamma ELISPOT
as a biomarker of treatment effi cacy in latent tuberculosis
infection: a clinical trial. Am J Respir Crit Care Med 2012;
32 Higuchi K, Harada N, Mori T. Interferon-gamma responses after
isoniazid chemotherapy for latent tuberculosis. Respirology 2008;
33 Ewer K, Millington KA, Deeks JJ, Alvarez L, Bryant G, Lalvani A.
Dynamic antigen-specifi c T-cell responses after point-source
exposure to Mycobacterium tuberculosis. Am J Respir Crit Care Med
2006; 174: 831–39.
34 Carrara S, Vincenti D, Petrosillo N, Amicosante M, Girardi E,
Goletti D. Use of a T cell-based assay for monitoring effi cacy of
antituberculosis therapy. Clin Infect Dis 2004; 38: 754–56.
35 Doherty TM, Demissie A, Olobo J, et al. Immune responses to the
Mycobacterium tuberculosis-specifi c antigen ESAT-6 signal
subclinical infection among contacts of tuberculosis patients.
J Clin Microbiol 2002; 40: 704–06.
36 Higuchi K, Harada N, Fukazawa K, Mori T. Relationship between
whole-blood interferon-γ responses and the risk of active
tuberculosis. Tuberculosis (Edinb) 2008; 88: 244–48.
37 Diel R, Loddenkemper R, Meywald-Walter K, Niemann S,
Nienhaus A. Predictive value of a whole blood IFN-gamma assay
for the development of active tuberculosis disease after recent
infection with Mycobacterium tuberculosis.
Am J Respir Crit Care Med 2008; 177: 1164–70.
38 Wallis RS, Palaci M, Vinhas S, et al. A whole blood bactericidal
assay for tuberculosis. J Infect Dis 2001; 183: 1300–03.
39 Janulionis E, Sofer C, Song HY, Wallis RS. Lack of activity of oral
clofazimine against intracellular M. tuberculosis in whole blood
culture. Antimicrob Agents Chemother 2004; 48: 3133–35.
40 Wallis RS, Vinhas SA, Johnson JL, et al. Whole blood bactericidal
activity during treatment of pulmonary tuberculosis. J Infect Dis
2003; 187: 270–78.
41 Immanuel C, Rajeswari R, Rahman F. Serial evaluation of serum
neopterin in HIV seronegative patients treated for tuberculosis.
Int J Tuberc Lung Dis 2001; 5: 185–90.
42 Hosp M, Elliott AM, Raynes JG, et al. Neopterin,
beta 2-microglobulin, and acute phase proteins in HIV-1-
seropositive and -seronegative Zambian patients with tuberculosis.
Lung 1997; 175: 265–75.
43 Demir T, Yalcinoz C, Keskinel I, Demiroz F, Yildirim N. sICAM-1
as a serum marker in the diagnosis and follow-up of treatment of
pulmonary tuberculosis. Int J Tuberc Lung Dis 2002; 6: 155–59.
44 Chan CH, Lai CK, Leung JC, Ho AS, Lai KN. Elevated interleukin-2
receptor level in patients with active pulmonary tuberculosis and
the changes following anti-tuberculosis chemotherapy. Eur Respir J
1995; 8: 70–73.
45 Brahmbhatt S, Black GF, Carroll NM, et al. Immune markers
measured before treatment predict outcome of intensive phase
tuberculosis therapy. Clin Exp Immunol 2006; 146: 243–52.
46 Ribeiro-Rodrigues R, Resende CT, Johnson JL, et al. Sputum cytokine
levels in patients with pulmonary tuberculosis as early markers of
mycobacterial clearance. Clin Diagn Lab Immunol 2002; 9: 818–23.
47 Lawn SD, Wiktor S, Coulibaly D, Ackah AN, Lal RB. Serum
C-reactive protein and detection of tuberculosis in persons
co-infected with the human immunodefi ciency virus.
Trans R Soc Trop Med Hyg 2001; 95: 41–42.
48 Bajaj G, Rattan A, Ahmad P. Prognostic value of ‘C’ reactive protein
in tuberculosis. Indian Pediatr 1989; 26: 1010–13.
49 Scott GM, Murphy PG, Gemidjioglu ME. Predicting deterioration
of treated tuberculosis by corticosteroid reserve and C-reactive
protein. J Infect 1990; 21: 61–69.
50 Eugen-Olsen J, Gustafson P, Sidenius N, et al. The serum level of
soluble urokinase receptor is elevated in tuberculosis patients and
predicts mortality during treatment: a community study from
Guinea-Bissau. Int J Tuberc Lung Dis 2002; 6: 686–92.
51 Djoba Siawaya JF, Bapela NB, et al. Immune parameters as markers
of tuberculosis extent of disease and early prediction of
anti-tuberculosis chemotherapy response. J Infect 2008; 56: 340–47.
52 Cheon SH, Kampmann B, Hise AG, et al. Bactericidal activity in
whole blood as a potential surrogate marker of immunity after
vaccination against tuberculosis. Clin Diagn Lab Immunol 2002;
53 Hoft DF, Worku S, Kampmann B, et al. Investigation of the
relationships between immune-mediated inhibition of mycobacterial
growth and other potential surrogate markers of protective
mycobacterium tuberculosis immunity. J Infect Dis 2002; 186: 1448–57.
54 Fletcher HA, Scriba TJ, Tanner R, et al. Evaluating mycobacterial
growth inhibition assays (MGIA) in TB vaccine studies.
Global Forum TB Vaccines 2013 (in press); 3 (abstract).
55 Kampmann B, Gaora PO, Snewin VA, Gares MP, Young DB,
Levin M. Evaluation of human antimycobacterial immunity using
recombinant reporter mycobacteria. J Infect Dis 2000; 182: 895–901.
56 Kampmann B, Tena GN, Mazazi S, Young D, Eley B, Levin M.
A novel human in vitro system to evaluate antimycobacterial
vaccines. Infect Immun 2004; 72: 6401–17.
57 Tena GN, Young DB, Eley B, et al. Failure to control growth of
mycobacteria in blood from children infected with human
immunodefi ciency virus, and its relationship to T cell function.
J Infect Dis 2003; 187: 1544–51.
www.thelancet.com/infection Vol 13 April 2013 371
58 Kampmann B, Tena-Coki GN, Nicol M, Levin M, Eley B.
Reconstitution of antimycobacterial immune responses in
HIV-infected children receiving HAART. AIDS 2006; 20: 1011–18.
59 Martineau AR, Wilkinson RJ, Wilkinson KA, et al. A single dose of
vitamin D enhances immunity to mycobacteria.
Am J Respir Crit Care Med 2007; 176: 208–13.
60 Sutherland JS, Hill PC, Adetifa IM, et al. Identifi cation of probable
early-onset biomarkers for tuberculosis disease progression.
PLoS One 2011; 6: e25230.
61 Diel R, Loddenkemper R, Niemann S, Meywald-Walter K,
Nienhaus A. Negative and positive predictive value of a whole-blood
interferon-γ release assay for developing active tuberculosis: an
update. Am J Respir Crit Care Med 2011; 183: 88–95.
62 Berry MP, Graham CM, McNab FW, et al. An interferon-inducible
neutrophil-driven blood transcriptional signature in human
tuberculosis. Nature 2010; 466: 973–37.
63 Mistry R, Cliff JM, Clayton C, et al. Gene expression patterns in
whole blood identify subjects at risk for recurrent tuberculosis.
J Infect Dis 2007; 195: 357–65.
64 Hirsch CS, Toossi Z, Vanham G, et al. Apoptosis and T cell
hyporesponsiveness in pulmonary tuberculosis. J Infect Dis 1999;
65 Agranoff D, Fernandez-Reyes D, Papadopoulos MC, et al.
Identifi cation of diagnostic markers for tuberculosis by proteomic
fi ngerprinting of serum. Lancet 2006; 368: 1012–21.
66 Weiner J III, Parida SK, Maertzdorf J, et al. Biomarkers of
infl ammation, immunosuppression and stress with active disease
are revealed by metabolomic profi ling of tuberculosis patients.
PLoS One 2012; 7: e40221.
67 Wang C, Yang S, Sun G, et al. Comparative miRNA expression
profi les in individuals with latent and active tuberculosis. PLoS One
2011; 6: e25832.
68 Hellyer TJ, Desjardin LE, Teixeira L, Perkins MD, Cave MD,
Eisenach KD. Detection of viable Mycobacterium tuberculosis by
reverse transcriptase-strand displacement amplifi cation of mRNA.
J Clin Microbiol 1999; 37: 518–23.
69 Walzl G, Ronacher K, Hanekom W, Scriba TJ, Zumla A.
Immunological biomarkers of tuberculosis. Nat Rev Immunol 2011;
70 Wallis RS, Pai M, Menzies D, et al. Biomarkers and diagnostics
for tuberculosis: progress, needs, and translation into practice.
Lancet 2010; 375: 1920–37.
71 Wallis RS, Doherty TM, Onyebujoh P, et al. Biomarkers for
tuberculosis disease activity, cure, and relapse. Lancet Infect Dis
2009; 9: 162–72.
72 Wallis RS, Wang C, Doherty TM, et al. Biomarkers for
tuberculosis disease activity, cure, and relapse. Lancet Infect Dis
2010; 10: 68–69.
73 Lee M, Lee J, Carroll M, et al. Linezolid for the treatment of chronic
extensively drug-resistant tuberculosis. N Engl J Med 2012;
74 Wallis RS, Nacy C. Early bactericidal activity of new drug regimens
for tuberculosis. Lancet 2013; 381: 111–12.
75 Wallis RS, Jakubiec W, Kumar V, et al. Biomarker assisted dose
selection for safety and effi cacy in early development of
PNU-100480 for tuberculosis. Antimicrob Agents Chemother 2011;
76 Mukamolova GV, Turapov O, Malkin J, Woltmann G, Barer MR.
Resuscitation-promoting factors reveal an occult population of
tubercle bacilli in sputum. Am J Respir Crit Care Med 2010;
77 Weyer K, Mirzayev F, Migliori G, et al. Rapid molecular TB
diagnosis: evidence, policy-making and global implementation of
Xpert(R)MTB/RIF. Eur Respir J 2012; published online Nov 22.
78 Lawn SD, Mwaba P, Bates M, et al. Advances in tuberculosis
diagnostics: the Xpert MTB/RIF assay and future prospects for a
point-of-care test. Lancet Infect Dis 2013; published online March 24.
79 Peter JG, Theron G, Muchinga TE, Govender U, Dheda K. The
diagnostic accuracy of urine-based Xpert MTB/RIF in HIV-infected
hospitalized patients who are smear-negative or sputum scarce.
PLoS One 2012; 7: e39966.
80 Peter JG, Theron G, van Zyl-Smit R, et al. Diagnostic accuracy of a
urine lipoarabinomannan strip-test for TB detection in HIV-
infected hospitalised patients. Eur Respir J 2012; 40: 1211–20.
81 Mukundan H, Kumar S, Price DN, et al. Rapid detection of
Mycobacterium tuberculosis biomarkers in a sandwich immunoassay
format using a waveguide-based optical biosensor. Tuberculosis
(Edinb) 2012; 92: 407–16.
82 Mikusova K, Slayden RA, Besra GS, Brennan PJ. Biogenesis of the
mycobacterial cell wall and the site of action of ethambutol.
Antimicrob Agents Chemother 1995; 39: 2484–89.
83 Via LE, Schimel D, Weiner DM, et al. Infection dynamics and
response to chemotherapy in a rabbit model of tuberculosis using
[(1)(8)F]2-fl uoro-deoxy-D-glucose positron emission tomography
and computed tomography. Antimicrob Agents Chemother 2012;
84 Maertzdorf J, Repsilber D, Parida SK, et al. Human gene expression
profi les of susceptibility and resistance in tuberculosis.
Genes Immun 2011; 12: 15–22.
85 John SH, Kenneth J, Gandhe AS. Host biomarkers of clinical
relevance in tuberculosis: review of gene and protein expression
studies. Biomarkers 2012; 17: 1–8.
86 Koth LL, Solberg OD, Peng JC, Bhakta NR, Nguyen CP,
Woodruff PG. Sarcoidosis blood transcriptome refl ects lung
infl ammation and overlaps with tuberculosis.
Am J Respir Crit Care Med 2011; 184: 1153–63.
87 Bloom CI, Graham CM, Berry MP, et al. Detectable changes in the
blood transcriptome are present after two weeks of antituberculosis
therapy. PLoS One 2012; 7: e46191.
88 Cliff JM, Lee JS, Constantinou N, et al. Distinct phases of blood
gene expression pattern through tuberculosis treatment refl ect
modulation of the humoral immune response. J Infect Dis 2013;
89 Rangaka MX, Wilkinson KA, Glynn JR, et al. Predictive value of
interferon γ release assays for incident active tuberculosis: a
systematic review and meta-analysis. Lancet Infect Dis 2012; 12: 45–55.
90 Diel R, Loddenkemper R, Nienhaus A. Predictive value of
interferon-γ release assays and tuberculin skin testing for
progression from latent TB infection to disease state: a meta-analysis.
Chest 2012; 142: 63–75.
91 Diel R, Goletti D, Ferrara G, et al. Interferon-gamma release
assays for the diagnosis of latent Mycobacterium tuberculosis
infection: a systematic review and meta-analysis. Eur Respir J 2011;
92 Yamada G, Shijubo N, Shigehara K, Okamura H, Kurimoto M,
Abe S. Increased levels of circulating interleukin-18 in patients
with advanced tuberculosis. Am J Respir Crit Care Med 2000;
93 Hirsch CS, Toossi Z, Johnson JL, et al. Augmentation of apoptosis
and interferon-gamma production at sites of active Mycobacterium
tuberculosis infection in human tuberculosis. J Infect Dis 2001;
94 Jones-Lopez EC, Ellner JJ, Whalen CC. Subclinical tuberculosis:
a new entity? Clin Infect Dis 2005; 41: 1069–70.
95 Mtei L, Matee M, Herfort O, et al. High rates of clinical and
subclinical tuberculosis among HIV-infected ambulatory subjects
in Tanzania. Clin Infect Dis 2005; 40: 1500–07.
96 Achkar JM, Jenny-Avital ER. Incipient and subclinical tuberculosis:
defi ning early disease states in the context of host immune
response. J Infect Dis 2011; 204 (suppl 4): S1179–86.
97 Kall MM, Coyne KM, Garrett NJ, et al. Latent and subclinical
tuberculosis in HIV infected patients: a cross-sectional study.
BMC Infect Dis 2012; 12: 107.
98 Alling DW, Bosworth EB. The after-history of pulmonary
tuberculosis. VI. The fi rst fi fteen years following diagnosis.
Am Rev Respir Dis 1960; 81: 839–49.
99 Singh KK, Dong Y, Belisle JT, Harder J, Arora VK, Laal S. Antigens
of Mycobacterium tuberculosis recognized by antibodies during
incipient, subclinical tuberculosis. Clin Diagn Lab Immunol 2005;
100 Raqib R, Kamal SM, Rahman MJ, et al. Use of antibodies in
lymphocyte secretions for detection of subclinical tuberculosis
infection in asymptomatic contacts. Clin Diagn Lab Immunol 2004;
www.thelancet.com/infection Vol 13 April 2013
101 Talat N, Shahid F, Dawood G, Hussain R. Dynamic changes in
biomarker profi les associated with clinical and subclinical
tuberculosis in a high transmission setting: a four-year follow-up
study. Scand J Immunol 2009; 69: 537–46.
102 Kunnath-Velayudhan S, Davidow AL, Wang HY, et al. Proteome-scale
antibody responses and outcome of Mycobacterium tuberculosis
infection in nonhuman primates and in tuberculosis patients.
J Infect Dis 2012; 206: 697–705.
103 Cooper AM. Cell-mediated immune responses in tuberculosis.
Annu Rev Immunol 2009; 27: 393–422.
104 Trautmann L, Janbazian L, Chomont N, et al. Upregulation of PD-1
expression on HIV-specifi c CD8+ T cells leads to reversible
immune dysfunction. Nat Med 2006; 12: 1198–202.
105 Qiu Y, Chen J, Liao H, et al. Tim-3-expressing CD4+ and CD8+
T cells in human tuberculosis (TB) exhibit polarized eff ector
memory phenotypes and stronger anti-TB eff ector functions.
PLoS Pathog 2012; 8: e1002984.
106 Henao-Temayo M, Irwin SM, Shang S, Ordway D, Orme I.
T lymphocyte surface expression of exhaustion markers as
biomarkers of the effi cacy of chemotherapy for tuberculosis.
Tuberculosis (Edinb) 2011: 91: 308–13.
107 Kleinsteuber K, Heesch K, Schattling S, et al. SOCS3 promotes
interleukin-17 expression of human T cells. Blood 2012;
108 Le Bourhis L, Martin E, Peguillet I, et al. Antimicrobial activity of
mucosal-associated invariant T cells. Nat Immunol 2010; 11: 701–08.
109 Gold MC, Cerri S, Smyk-Pearson S, et al. Human mucosal
associated invariant T cells detect bacterially infected cells.
PLoS Biol 2010; 8: e1000407.
110 Brennan MJ, Thole J. Tuberculosis vaccines: a strategic blueprint
for the next decade. Tuberculosis (Edinb) 2012; 92 (suppl 1): S6–13.
111 Kagina BM, Abel B, Scriba TJ, et al. Specifi c T cell frequency and
cytokine expression profi le do not correlate with protection against
tuberculosis, following BCG vaccination of newborns.
Am J Respir Crit Care Med 2010; 182: 1079–79.
112 Cheng SH, Walker L, Poole J, et al. Demonstration of increased
anti-mycobacterial activity in peripheral blood monocytes after BCG
vaccination in British school children. Clin Exp Immunol 1988;
113 Hoft DF, Blazevic A, Abate G, et al. A new recombinant bacille
Calmette-Guerin vaccine safely induces signifi cantly enhanced
tuberculosis-specifi c immunity in human volunteers. J Infect Dis
2008; 198: 1491–501.
114 Saliu O, Sofer C, Stein DS, Schwander SK, Wallis RS. Tumor
necrosis factor blockers: diff erential eff ects on mycobacterial
immunity. J Infect Dis 2006; 194: 486–92.
115 Wallis RS, Vinhas S, Janulionis E. Strain specifi city of
antimycobacterial immunity in whole blood culture after cure of
tuberculosis. Tuberculosis (Edinb) 2009; 89: 221–24.
116 Floto RA, MacAry PA, Boname JM, et al. Dendritic cell stimulation
by mycobacterial Hsp70 is mediated through CCR5. Science 2006;
117 BCG and vole bacillus vaccines in the prevention of tuberculosis in
adolescence and early adult life. Bull World Health Organ 1972;
118 Sepulveda RL, Parcha C, Sorensen RU. Case-control study of the
effi cacy of BCG immunization against pulmonary tuberculosis in
young adults in Santiago, Chile. Tuber Lung Dis 1992; 73: 372–77.
119 Rodrigues LC, Pereira SM, Cunha SS, et al. Eff ect of BCG
revaccination on incidence of tuberculosis in school-aged children
in Brazil: the BCG-REVAC cluster-randomised trial. Lancet 2005;
120 Karonga Prevention Trial Group. Randomised controlled trial of
single BCG, repeated BCG, or combined BCG and killed
Mycobacterium leprae vaccine for prevention of leprosy and
tuberculosis in Malawi. Lancet 1996; 348: 17–24.
121 Cunha SS, Alexander N, Barreto ML, et al. BCG revaccination does
not protect against leprosy in the Brazilian Amazon: a cluster
randomised trial. PLoS Negl Trop Dis 2008; 2: e167.
122 Leung CC, Tam CM, Chan SL, Chan-Yeung M, Chan CK,
Chang KC. Effi cacy of the BCG revaccination programme in a
cohort given BCG vaccination at birth in Hong Kong.
Int J Tuberc Lung Dis 2001; 5: 717–23.
123 Batz H-G, Cooke GS, Reid SD for Médecins Sans Frontières.
Towards lab-free tuberculosis diagnosis. August, 2011. http://www.
Report_TowardsLabFreeTBDX_2011_ENG.pdf (accessed Dec 8,
124 Pellin D, Miotto P, Ambrosi A, Cirillo DM, Di SC. A genome-wide
identifi cation analysis of small regulatory RNAs in Mycobacterium
tuberculosis by RNA-Seq and conservation analysis. PLoS One 2012;
125 Nemeth J, Winkler HM, Zwick RH, et al. Peripheral T cell cytokine
responses for diagnosis of active tuberculosis. PLoS One 2012;
126 Nemeth J, Winkler HM, Boeck L, et al. Specifi c cytokine patterns of
pulmonary tuberculosis in Central Africa. Clin Immunol 2011;
127 Harari A, Rozot V, Enders FB, et al. Dominant TNF-alpha+
Mycobacterium tuberculosis-specifi c CD4+ T cell responses
discriminate between latent infection and active disease. Nat Med
2011; 17: 372–76.
128 Giri PK, Kruh NA, Dobos KM, Schorey JS. Proteomic analysis
identifi es highly antigenic proteins in exosomes from
M. tuberculosis-infected and culture fi ltrate protein-treated
macrophages. Proteomics 2010; 10: 3190–202.
129 Nahid P, Saukkonen J, Mac Kenzie WR, et al. CDC/NIH Workshop.
Tuberculosis biomarker and surrogate endpoint research roadmap.
Am J Respir Crit Care Med 2011; 184: 972–79.
130 US Department of Health and Human Services. Research in latent
tuberculosis infection (LTBI) in the setting of HIV co-infection
(R01). DC: US Department of Health and Human Services,
December 2012. http://grants1.nih.gov/grants/guide/pa-fi les/PAR-
13-061.html (accessed Mar 4, 2013).