DiagnosticsA real-time PCR signature to discriminate between tuberculosis and other pulmonary diseases
Introduction
Despite increasing treatment success rates, tuberculosis (TB) continues to spread worldwide. The World Health Organization (WHO) estimates that 8.6 million people developed TB and 1.3 million died from the disease in 2012 [15]. Lack of accurate and rapid test to diagnose TB remains an important obstacle to TB control. The most common clinical dilemma encountered in TB diagnosis is the differentiation of pulmonary TB from other common lung diseases. When a patient is found to have an abnormal chest X-ray, TB is not necessarily on the top of the list of differential diagnosis in most settings.
Unbiased microarray gene expression profiling of whole blood cells has provided candidate biosignatures to discriminate TB patients from healthy donors [1], [4], [9], [10], [12]. However, these studies that compare TB to healthy controls mostly reveal a general state of persistent inflammation and not TB per se [14].
Recently, several groups have sought TB-specific biomarkers by comparing them in patients with TB versus other inflammatory pulmonary diseases [3], [6], [7], [11]. Despite overlapping gene up-regulation in proinflammatory pathways and general immunopathological mechanisms, they could identify transcript signatures to distinguish TB from other diseases, including in HIV infected and uninfected subjects [6].
Here, we selected a restricted set of genes to assess their ability to differentiate TB from other pulmonary diseases (OPD) patients. These genes were previously identified by Maertzdorf et al. [10] as a biosignature to discriminate TB and healthy latently infected (LTBI) subjects: granzyme A (GZMA), guanylate binding protein 5 (GBP5), Fc gamma receptor 1A (CD64), Fc gamma receptor 1B (FCGR1B) and lactotransferrin (LTF). Maertzdorf et al. [10] did not include OPD patients in their study, but since then, CD64, FCGR1B and LTF were shown to be differentially expressed in TB versus other lung diseases [3], [5], [11].
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Study participants
Subjects were recruited between March 1, 2011 and March 30, 2013. Written informed consent was obtained from all participants. Our cohort included 27 patients with active tuberculosis (TB), 27 healthy donors with latent Mycobacterium tuberculosis infection (LTBI), 25 healthy non-infected donors (NIDs), and 22 patients suffering from other pulmonary diseases (OPD)--14 patients with asthma and eight patients with streptococcal pneumonia (PN). All subjects were older than 18, and responded to a
Results
We assessed the gene expression level of CD64, FCGR1B, GZMA, GBP5 and LTF by real-time PCR in whole blood samples from 25 NIDs, 27 LTBI, 27 TB, 14 asthma and eight PN donors (Table 1). B2M was chosen as reference gene based on Maertzdorf et al.'s study [10]. There was a difference in age distribution between the study groups, but we found no evidence to suggest gene expression levels correlated with the donor's age. Although we did find evidence that suggests FCGR1B and LTF expression is
Discussion
Clinically relevant TB biomarkers need to be able to distinguish pulmonary TB and non-TB pulmonary diseases. Otherwise, such tests would be no more specific than a chest x-ray. Here, we wished to be able to distinguish TB from other common pulmonary diseases. Asthma represents a chronic non-infectious inflammatory airways disease. Non-TB pneumonias represent the most common infectious pulmonary disease that healthcare providers need to rapidly distinguish from TB, when patients seek health care
Funding
This work was supported by the Fogarty International Center at the National Institutes of Health [grant number U2RTW006885] and the UBS Optimus Foundation.
Competing interests
None of the authors that contributed to this work have any conflict of interest to declare.
Ethical approval
The study was accepted by the ethical committees of the Prefeitura de Porto Alegre (IRB approval 630), the Hospital de Clínicas in Porto Alegre (IRB approval 110201) and the Fundação Estadual de Produção e Pesquisa em Saúde (IRB approval 03/2011).
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These authors contributed equally to this work.