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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 8  |  Issue : 2  |  Page : 146-152

Evaluation of apoptotic protease-activating Factor-1 and cluster of Differentiation-4+ T-Cell counts in patients-infected with mycobacterium tuberculosis in Bauchi, Nigeria


1 Department of Medicine, Immunology Unit, Ahmadu Bello University, Zaria, Nigeria
2 Department of Medicine, Ahmadu Bello University, Zaria, Nigeria
3 Department of Medical Laboratory Science, Ahmadu Bello University, Zaria, Nigeria

Date of Web Publication14-Jun-2019

Correspondence Address:
Muhammad Sagir Shehu
Immunology Unit, Department of Medicine, Ahmadu Bello University, Zaria
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijmy.ijmy_66_19

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  Abstract 


Background: This cross-sectional study evaluated Apoptotic Protease Activating Factor and cluster of differentiation-4+ (CD4+) T-cell counts in patients infected with Mycobacterium tuberculosis in Bauchi, Nigeria. Methods: This involved 180 blood samples from 90 tuberculosis (TB)-infected patients and 90 of their close contacts at home or attending Federal Medical Center Azare and Infectious Disease Hospital Bayara, Bauchi, Nigeria. The blood samples were analyzed for Apoptotic Protease Activating Factor (Apaf-1) expression using ELISA and CD4+ T cells using cyflow counter. Structured questionnaires were also used to collect the sociodemographic and clinical data of the study participants. Results: Eighty-six of the TB-infected patients had pulmonary TB (PTB), two had spine TB, and two had pleural TB. No statistically significant difference was recorded in CD4+ T-cell counts (P = 0.2935) between participants with PTB (mean ± standard deviation [SD]: 680.4 ± 235 cells/mm3) and those with extra-PTB (mean ± SD: 553.0 ± 130.5 cells/mm3). Similarly, there was no significant difference in Apaf-1 concentration (P = 0.1432) between participants with PTB (mean ± standard error of the mean [SEM]: 320.3 ± 35.4 pg/ml), and participants with extra-PTB (mean ± SEM: 143.7 ± 7.8 pg/ml). No significant difference was recorded in CD4+ T-cell counts (P = 0.4299) between the participants on treatment (mean ± SD: 758.6 ± 358.6 cells/mm3) and those who are treatment naïve (mean ± SD: 637.7 ± 208.4 cells/mm3). Similarly, there was no significant difference in Apaf-1 concentration (P = 0.6829) between the study participants on treatment (mean ± SEM: 336.3 ± 34.7 pg/ml) and those who are not on treatment (mean ± SEM: 381.2 ± 176.8 pg/ml). The CD4+ T-cells count was significantly higher in the controls (866.7 ± 288.4 cells/mm3) compared to the TB (675.0 ± 232.7 cells/mm3) patients (P < 0.0001). However, there was no significant difference in Apaf-1 expression between the control (312.4 ± 34.6 pg/ml) and the TB patients (329.1 ± 44.0 pg/ml) (P = 0.7658). Conclusion: Findings from this study showed a lower T-cell immune function during TB infection. However, Apaf-1 has no relevance on TB progression and control.

Keywords: Apaf-1, cluster of differentiation-4+ T-cells, cellular immunity, tuberculosis


How to cite this article:
Shehu MS, OKpapi JU, Priscilla Musa BO, Abdullahi IN, Ahmad AE, Usman Y. Evaluation of apoptotic protease-activating Factor-1 and cluster of Differentiation-4+ T-Cell counts in patients-infected with mycobacterium tuberculosis in Bauchi, Nigeria. Int J Mycobacteriol 2019;8:146-52

How to cite this URL:
Shehu MS, OKpapi JU, Priscilla Musa BO, Abdullahi IN, Ahmad AE, Usman Y. Evaluation of apoptotic protease-activating Factor-1 and cluster of Differentiation-4+ T-Cell counts in patients-infected with mycobacterium tuberculosis in Bauchi, Nigeria. Int J Mycobacteriol [serial online] 2019 [cited 2019 Sep 18];8:146-52. Available from: http://www.ijmyco.org/text.asp?2019/8/2/146/260388




  Introduction Top


Tuberculosis (TB) is a granulomatous disease caused by a large group of mycobacteria; Mycobacterium tuberculosis (MTB) (MTB complex) comprising MTB, Mycobacterium africanum, Mycobacterium bovis, Mycobacterium canettii, Mycobacterium microti, Mycobacterium orygis, Mycobacterium caprae, Mycobacterium pinnipedii, Mycobacterium surricattae and Mycobacterium mungi.[1],[2] The disease is a global health problem that affects millions of people each year and is one of the leading causes of death worldwide.[3] Considering the role of MTB-induced apoptosis, especially on innate immune cells, and possible anti-TB failure due to joint intrinsic MTB defense mechanism and poor host cells immune function, this study was carried out to provide data on the possible involvement of apaf-1 expression and cluster of differentiation-4+ (CD4+) T-cell counts in TB immunity, prognosis, and resolution.

Infection with MTB is initiated when the bacilli are inhaled as droplets nuclei from the atmosphere. The innate immune response is initiated when MTB in the alveolar space is recognized by pattern recognition receptors, mostly toll-like receptors expressed by alveolar and interstitial macrophages, as well as local dendritic cells (DCs), and, subsequently, phagocytosed.[4] The DCs which serve as antigen presenting cells present antigen in association with major histocompatibility complex (MHC) class II molecules to CD4+ T-helper lymphocytes, and in association with MHC-I and CD1 to CD8 + T-cells.[5]

Apoptotic protein 1 otherwise known as Apoptotic protease-activating factor 1 (Apaf-1) is a human homolog of CED-4 gene of Caenorhabditis elegans.[6] During TB infection Apaf-1 binds to Cytochrome c resulting in subsequent replacement of Apaf-1-associated ADP by deoxy-ATP/ATP, which triggers the formation of a multimeric signaling complex called the apoptosome. The recruitment and cleavage of procaspase-9 by the apoptosome activates the executioner caspases,[7] this leads to macrophage death.

In serious cases of pulmonary TB (PTB), the exacerbation of necrotic cell death leads to extensive caseous lesions and in consequence, to the rupture of granulomas into airways as well as the cavitation and dissemination of mycobacteria.[8] The question, therefore, is whether a failure of macrophage apoptotic death and resultant necrotic mechanisms are responsible for poor TB control. Since host cell apoptosis is associated with a protective response to MTB infection, whereas a necrotic response favors the pathogen. Consistently, MTB inhibits host cell apoptosis signaling but promotes induction of programmed necrosis. The molecular mechanisms involved in MTB-mediated host cell death manipulation, the consequences for host immunity, and the potential for therapeutic and preventive measures are crucial biomedical issues that require investigations. For example, overexpression of Apaf-1 could indicate potential anti-TB therapeutic failure, whereas CD4+ T cells lymphopenia is an indication of immunosuppression.[9] In view of these, there is a need to assess the clinical significance and correlation of apoptotic protein 1 and CD4+ T-cell counts among TB patients with a view to proffering better solutions that will alleviate the sufferings associated with TB as well as better the understanding of the immunopathogenesis of MTB infection.


  Methods Top


Study Area

This study was conducted at Federal Medical Center, Azare and Infectious Disease Hospital Bayara Bauchi state, Nigeria.

Study design

This was a hospital-based cross-sectional comparative study.

Study population

The study population involved 90 patients with laboratory and clinically confirmed active TB in comparison with another group involving 90 people working in TB laboratories and close contacts of TB patients.

Sample size determination

The sample size was determined using the Fischer's expression and the prevalence of MTB in prison inmates at Aba Federal Prison, Abia State at 2.2%[10] and with the prevalence of MTB in healthcare workers at 3.3%.[11] Hence, a minimum sample size of 34 and 48 for TB patients and their close contacts, respectively. However, to enhance the statistical credence of the study, 90 TB patients and ninety of their close contacts were recruited for the study. The Fischer's formula for sample size determination as proposed by Charan and Diswas[12] was used for this study.



Where N = sample size of participants required for the study

Z-statistic for a level of 95% confidence interval = 1.96

P1= Prevalence rate = 0.022[10]

d = precision (allowable error) =5% =0.05



N1 =34

At 10% attrition, N1 = 38. However, to enhance the statistical credence of the study Ninety participants were recruited for the study.

P2= Prevalence rate = 0.033[11]

d = precision (allowable error) =5% =0.05



N2 =48

However, to enhance the statistical credence of the study 90 participants were recruited from MTB close contacts.

Note:

Close contacts of TB patients were enrolled as controls because of the likelihood of them having latent TB. Since apoptotic genes differentiate between active and latent TB infection,[13] this study was able to determine whether Apaf-1 concentration can significantly correlate with the status of MTB infection.

Sampling technique

Convenient random sampling technique was used since only three patients come to the Dot clinics on average per day. The TB-infected patients were approached with informed consent forms and questionnaires as they come. The national algorithm was used to screen participants for HIV while TB was confirmed by clinicians and later in the laboratory by gene expert.

Ethical consideration

Ethical clearance was obtained from the Ethical Review Committee of Bauchi State Ministry of Health, Nigeria (approval number: MOH/GEN/S/409/1. Informed consent was also obtained from all participants in accordance with the standards of human experimentation and with the Helsinki Declaration of 1975, as revised in 2014.

Blood sample collection

After the patients and their close contacts working in TB laboratory have consented, they were requested to fill in the questionnaire, and 5 ml of blood samples were collected from them as follows.

Laboratory coat and hand gloves were worn, a tourniquet was applied to the patient's arm, and the arm was positioned on the armrest.

The vein was palpated to enhance vasodilation; the skin overlying the vein was cleaned with 70% alcohol and allowed to dry. The syringe and the needle were removed from their pouch, the needle was attached to the syringe and the guard removed. The needle was inserted into the vein while the bevel was facing upwards. With one hand steadying the barrel of the syringe so that the needle is not accidentally withdrawn from the vein, 5 ml of blood was withdrawn into the syringe using minimal negative pressure. The tourniquet was released and the needle withdrawn from the vein. Following removal of the needle, direct pressure was applied to the puncture site with cotton wool, the arm being kept straight and somewhat elevated. The needle was removed from the syringe before expelling the blood into the specimen container, great care being taken to avoid self-injury with the needle. The needle was put directly into a special receptacle for sharp objects without resheathing it. The blood specimen was expelled gently into a tube containing ethylenediaminetetraacetic acid (EDTA) anticoagulant and mixed gently by inverting the container four or five times. The container was labeled appropriately for the name, identification number, time of collection, and date. The whole blood was used for CD4+ T-cell counts. The remaining volume of blood sample was separated by centrifugation at 4000 revolutions per minute for 20 min, 2 ml of plasma was then aliquoted into cryovial containers and stored in a freezer at a maximum temperature of −20°C. The plasma samples were transported in a box of ice packs to Immunology laboratory, Ahmadu Bello University Teaching hospital Zaria for the evaluation of Apoptotic protein 1.

Determination of cluster of differentiation-4+ T cell count

CD4+ T cell count in whole blood was determined using Partec Cyflow® analyzer model SL3 based on the manufacturer's instruction. This works on the principle of light scatter (due to different size or granularity of the cells) combined with fluorescence of cells after staining with monoclonal antibodies to cell surface markers tagged to fluorescent dye.

Procedure

Cyflow reagents and consumables were used according to the manufacturer's instructions. 20 μL of EDTA anticoagulated blood specimen obtained from each study participant was dispensed into a Partec test tube. Ten microliters of CD4-phycoerythrin conjugated monoclonal antibody supplied by Partec was added to the tube containing the blood and then incubated for 15 min at room temperature in the dark. Following incubation, 800 μL of no lyse buffer, supplied by Partec was added to the tube and gently vortex-mixed. The tube was then plugged into the Cyflow counter for automatic counting.

The histogram and absolute counts were displayed and printed automatically. The histogram showed direct counting of the result in terms of absolute CD4+ T-lymphocytes/μL. The CD4+ T-lymphocytes with high fluorescence appear in a prominent peak at the right of the histogram, whereas the weaker but also CD4+ monocytes appear to the left without any overlap with CD4+ T-lymphocytes. CD4+ (CD3+ CD4+ CD8-) cells were gated (regions drawn on fluorescence scatter plots and histograms to selectively focus on populations of interest) by the process of primary CD4 gating'. Absolute CD4+ cell counts were then determined using single-platform methodology. Internal quality control for pipetting errors was based on CD3 replicates using the Immunocount II quality control programme.

Principle of apoptotic protein-1 quantitative ELISA

This assay employs the quantitative sandwich enzyme immunoassay technique. Antibody specific for Apaf-1 has been precoated onto the 96 wells microplate. When standards and plasma/serum samples were dispensed into the wells, any Apaf-1 present will bind the immobilized antibody. After removing any unbound substances, a biotin-conjugated antibody specific for Apaf-1 is added to the wells. After washing, avidin-conjugated Horseradish Peroxidase was added to the wells. Following a wash to remove any unbound avidin-enzyme reagent, a substrate solution was added to the wells and color develops in proportion to the amount of Apaf-1 bound in the initial step. The color development was stopped, and the intensity of the color was measured.

Detection range

30 pg/ml–2000 pg/ml.

Sensitivity

The serum minimum detectable limit of human Apaf-1 is 6 pg/ml. The sensitivity and specificity of this assay were defined as 96.5% and 100%, respectively. No significant cross-reactivity or interference between human Apaf-1 and analogs has been observed.

Calculation of results

The concentration of Apaf-1 was determined using the standard curve method. Each standard and sample was subtracted from the average zero standard optical density. A standard curve was constructed by plotting the absorbance for each standard on the y-axis against the concentration of Apaf-1 on the x-axis and the best-fit curve was drawn through the points on the graph.

Statistical analysis

Data obtained from the questionnaire and results of the laboratory analysis was analyzed using GraphPad Prism (Version 6) statistical software, San Diego USA. Two-tailed Chi-square test was used to determine the statistical relationship between nonnumerical variables such as sociodemographics and the outcome. Student's t-test was used to test for statistical difference between numerical values of CD4+ T cells and Apaf-1 concentrations. Correlation analysis was used to correlate CD4+ T cells and Apaf-1 concentrations. Probability value <0.05 was considered statistically significant.


  Results Top


One hundred and eighty individuals were recruited for the study. These include 90 (50%) MTB-infected individuals as test group and another 90 (50%) MTB-negative individuals who are TB close contacts as control group.

The female participants were 22 (12.2%) in the test group and 16 (8.9%) in the control group. There is no significant difference between the two groups (χ2 = 1.201, df = 1, P = 0.2731, odds ratio = 0.6683 (95% confidence interval: 0.3242–1.378) [Table 1]. The age group with the highest number of TB-infected individuals is 18–27 years and 28–37 years with a prevalence of 33.4% each. The age group with the least TB prevalence is ≥58. In the group, only 6 (3.3%) were infected with TB. There is no significant relationship between the age groups and TB infection (χ2 = 7.341, df = 4, P = 0.1189) [Table 1].
Table 1: Sex and age distribution of the study participants

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Mean age, anthropometry, and immunological parameters of the study participants

The means and standard deviations (SDs) of ages for TB-infected patients and their apparently healthy control counterparts were 35.0 ± 11.5 and 33.1 ± 10.0 years, respectively, there was no significant difference between the two groups (P = 0.2385) [Table 1]. However, there was significant difference in body mass index (BMI) (P < 0.0014) between the test and control groups, the means and SDs were 18.9 ± 2.3 kg/m2 and 21.5 ± 2.9 kg/m2, respectively [Table 2]. The means and SDs of test and control groups for CD4+ T-cell counts were 675.0 ± 232.7 cells/μ and 866.7 ± 288.4 cells/μL, respectively, there was a significant difference between the two groups [Figure 1] (P < 0.0001). There was no significant difference in Apaf-1 concentration (P = 0.7658) between the test (median- and inter-quartile range: 312.4 ± 34.6 pg/ml) and the control group (median and interquartile range: 329.1 ± 44.0 pg/ml) [Figure 2].
Table 2: Mean age and anthropometry of the study participants

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Figure 1: Cluster of differentiation-4+ T cells in test and control groups

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Figure 2: Apaf-1 results in tuberculosis positive participants and controls

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Immunological parameters by tuberculosis type

There was no significant difference in CD4+ T-cell counts (P = 0.2935) between participants with PTB (mean ± SD: 680.7 ± 235.3 cells/μL) and those with extra-PTB (mean ± SD: 553.0 ± 130.5 cells/μL). Similarly, there was no significant difference in Apaf-1 concentration (P = 0.1432 pg/ml) between participants with PTB (mean ± standard error of the mean [SEM]: 320.3 ± 35.8 pg/ml) and those infected with extra-PTB (mean ± SEM: 143.7 ± 7.8 pg/ml).

Immunological parameters of study participants on-treatment and not on treatment

There was no significant difference in CD4+ T-cell counts (P = 0.4299 cells/μL) between the participants with TB on treatment (mean ± SD: 758.6 ± 358.6 cells/μL) and those who are treatment naïve (mean ± SD: 637.7 ± 208.4 cells/μL) [Figure 3]. Similarly, there was no significant difference in Apaf-1 concentration (P = 0.9311 pg/ml) between the study participants on treatment (mean ± SEM: 336.3 ± 34.7 pg/ml) and those who are not on treatment (mean ± SEM: 381.2 ± 176.8 pg/ml) [Figure 4].
Figure 3: Dot-blot graph showing cluster of differentiation-4+ T cells distribution of tuberculosis patients and controls

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Figure 4: Dot-blot graph showing Apaf-1 result between patients with tuberculosis on treatment and without

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  Discussion Top


The mean value and SDs of ages for TB-infected patients was 35.0 ± 11.5 years. This is not unexpected because the majority of TB-infected individuals are young adults, probably because they are relatively involved or exposed to higher risk of contracting the bacilli. This observation is in consonance with the findings of Nwachukwu et al.[14] where they reported that persons within 18–50 years of age had the highest proportion of PTB. They attributed this result to the fact that they are able-bodied men and women with higher exposure to the environment where they could contract the airborne tuberculous bacilli. It was reported in Kano, Nigeria, that the highest prevalence rate of PTB occurred more among patients within 21–30 years of age.[15] This is evident from the study of TB among healthcare workers with pronounced occupational exposure, where participants aged 20 years and above had a higher risk for occupationally-acquired PTB than those who were 20 years and below.[11]

Findings from this study revealed that 86 of the TB-infected patients had PTB, two had spine TB and the remaining two had pleural TB. The difference in these figures reflects the state of endemicity between the study locations. The majority of TB being PTB reflects the fact that PTB is the common clinical presentation of TB. This is partly because the respiratory tract is the major route of transmission of TB, and so carries the major burden of the disease. The incidence of pulmonary and extra-PTB in developing countries has increased by 4-fold in between 1976 and 2012. This relative increase may be an underestimate.[16] In Africa, due to the low standard of living, famine, and inadequate shelter with attendant overcrowding, the TB scourge has increased. In Nigeria, Umo et al.[17] reported 62% incidence of PTB in Ekpene Obom (Etinam), Akwa-Ibom, Nigeria.

Findings from this study also revealed no significant difference in CD4+ T-cell counts between participants with PTB and extra-PTB; however, those with extra-PTB had the lowest CD4+ T cell counts. This could be because extra-PTB is more likely to persist and even reoccur and thus produce prolong CD4+ T cell lymphopenia.

There was no significant difference in CD4+ T-cell counts between the participants on treatment and those who were anti-TB treatment naïve. However, the CD4+ T-cell counts of those on treatment were relatively higher than those who were treatment naïve (758.6 ± 358.6 cells/μL versus 637.7 ± 208.4 cells/μL). This could be due to immune reconstitution, thereby leading to better CD4+ T-cell population due to anti-TB treatment. Cell-mediated immune responses are protective in TB, and production of cytokines and chemokines by macrophages and DCs is crucial to initiating cellular immune responses to MTB.[18] The continuous increase of CD4+ T-cell counts during the course of anti-TB treatment suggest a reversible impact of active TB on CD4+ T cell homeostasis.[19] The CD4+ T-cell counts were significantly high in the controls compared to the TB patients. Since the controls have high CD4+ T-cell counts than the test group, this depicts a decrease in CD4+ T-cell immune function during active TB, infection.

However, there was no significant difference in Apaf-1 concentration (P = 0.1432) between these groups of participants. In fact, the mean Apaf-1 expression was the highest in those with PTB. This could be because cells that have greater affinity for tubercle bacilli are more in the lungs than any other tissue or organ, thus there is a higher apoptotic process aimed at tissue repair. Similar observation was reported by Lam et al.[20] The number of participants that have extraPTB is few (4) compared to those with PTB (86), to power any of the results of CD4+ T-cell counts and Apaf-1 concentration in the study population.

Production of cytokines and chemokines by macrophages and DCs is crucial to initiating cellular immune responses to M MTB.[18] These events will change the equilibrium of pro-and anti-apoptotic Bcl-2 family members toward activation of the majority of pro-apoptotic proteins. These associates with the apoptosis protease activating factor-1 (Apaf-1) to form the apoptosome complex.[21] In fact, this is evident by the relatively low-Apaf-1 expression in those on anti-TB treatment (336.3 ± 34.7 pg/ml) compared to those who are treatment-naive (381.2 ± 176.8 pg/ml).

There was no significant difference in Apaf-1 expression between the control and the TB patients. This observed finding might explain that Apaf-1 expression in TB becomes pronounced and upsurges at the chronic and prolonged stage of the disease. In addition, the low concentration of Apaf-1 in the study participants might be due to the low level of DNA damage in TB. Since Apaf-1 is a downstream effector of p53 in DNA damage-induced apoptosis,[22] disruption of this protein in cells dramatically reduces p53-dependent apoptosis.[23]

A significant difference was recorded in BMI between the study participants and controls (P < 0.0001). Similar observations were reported by Casha and Scarci[24] and Kim et al.[25] This strong association between TB and BMI occurred only with PTB and not extra-PTB, indicating that a low-BMI body build may in some way predispose to TB reactivation in the lungs. This may be due to the congenital apical lung bullae that occur in some individuals of the population and are likely to enlarge in young low-BMI males.[25]


  Conclusion Top


The study shows lower CD4+ T-cell immune function in TB patients in Bauchi state. This correlated with the BMI in TB patients compared to the control participants. However, there was no significant difference in Apaf-1 concentration between the tests and the controls and between different types of TB. This shows that Apaf-1 has no relevance on TB progression and control. However, the slight increase in Apaf-1 expression in TB-infected participants is a subject for further research where more patients will be included and the patients' selection should differ.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2]



 

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