The assessment of cytokines in Quantiferon supernatants for the diagnosis of latent TB infection in a tribal population of Melghat, India

Summary: The tuberculin skin test (TST) and interferon-gamma release assays (IGRA), namely, the QuantiFERON-TB Gold test (QFT), remain the standard immunological diagnostic tools for latent tuberculosis (TB) infection (LTBI). However, the sub-optimal detection rates of both of these tests are major impediments in recognizing the population at risk. This study was aimed at evaluating additional cytokines besides interferon-gamma (IFN-γ) as biomarkers for improving LTBI diagnosis in the tribal population of Melghat, India. Seventy-four close TB contacts were stratified by QFT and TST results into: (i) QFT+/TST+ (n = 26), (ii) QFT+/TST− (n = 12), (iii) QFT−/TST− (n = 35) and (iv) QFT−/TST+ (n = 1) groups. A panel of cytokines (IL-6, IL-10, TNF-α and IL-2R) was then evaluated in antigen-stimulated QFT cell-free culture supernatants using IMMULITE-1000, an automated immunoassay analyzer. Cytokine estimation showed significantly higher levels of IL-6 in the QFT+/TST+ group, while significantly higher levels of IL-10 were found in the QFT−/TST− group. Correlation analysis identified a positive correlation between IL-6 and the QFT response (r = 0.6723, P < 0.0001), while a negative correlation was seen between QFT and IL-10 expression (r = −0.3271, P = 0.0044). Similarly, IL-6 was positively correlated with TST levels (r = 0.6631, P < 0.0001), and conversely, a negative correlation was found between TST and IL-10 expression (r = −0.5698, P < 0.0001). The positive and negative predictive values of IL-6 were found to be 92.59 and 93.33%, respectively, and the positive and negative predictive values of IL-10 were 96.55 and 91.18%, respectively. No significant impact of the demographic characteristics on cytokine positivity was observed. Our preliminary results suggest that the evaluation of additional cytokines in QFT cell-free culture supernatants may be valuable for the identification of LTBI. Combining IL-6 and IL-10 with QFT and/or TST could markedly improve the detection accuracy of LTBI. Our observations require investigation in larger well-characterized cohorts along with follow-up studies to further confirm the study outcome. Keywords: Cytokines, LTBI, TST, QF

Impact of socioeconomic status and living condition on latent tuberculosis diagnosis among the tribal population of Melghat: A cohort study

Aims: To study socioeconomic status (SES) and living conditions (LC) as risk factors for latent tuberculosis infection (LTBI) and their impact on QuantiFERON-TB gold (QFT-G) and tuberculin skin test (TST) outcome for determining a better diagnostic test for LTBI in the malnourished tribal population of Melghat. Settings and Design: Six hundred sixty nine participants matching the inclusion criteria were recruited from 10 tribal villages of Melghat region, India. Subjects and Methods: Complete information related to various risk factors and test outcome was obtained on 398 participants, which was analyzed as per predefined conceptual framework. Factors were classified based on their relevance either at individual or household level, and subsequently based on the possibility of intervention. Data were partitioned into concordant and discordant sets depending on test agreement. Results: In concordant set, the two tests revealed that LTBI was significantly associated with smoking (adjusted odds ratio [aOR]: 2.64 [95% confidence interval [CI]: 1.03-6.79]), tobacco usage (aOR: 2.74 [95% CI: 1.50-4.99]), and malnourishment (aOR: 1.97 [95% CI: 1.12-3.48]) after basic adjustment. Inclusion of latent variable SES and LC in the model has mediating effect on the association of above factors with LTBI. Further, the association of SES and LC with LTBI in concordant set was unaltered in presence of other cofactors. From discordant set, results of QFT-G corroborated with that of concordant set. Conclusions: Poor SES and LC can be considered as strong risk factors linked with LTBI as compared to malnourishment, which is often targeted in such communities. Further, our study showed QFT-G test as a reliable tool in screening of LTBI in the tribal population of Melghat, India

Nested PCR Assay for Eight Pathogens: A Rapid Tool for Diagnosis of Bacterial Meningitis

Purpose Bacterial meningitis is a dreadful infectious disease with a high mortality and morbidity if remained undiagnosed. Traditional diagnostic methods for bacterial meningitis pose a challenge in accurate identification of pathogen, making prognosis difficult. The present study is therefore aimed to design and evaluate a specific and sensitive nested 16S rDNA genus-based polymerase chain reaction (PCR) assay using clinical cerebrospinal fluid (CSF) for rapid diagnosis of eight pathogens causing the disease. Methods The present work was dedicated to development of an in-house genus specific 16S rDNA nested PCR covering pathogens of eight genera responsible for causing bacterial meningitis using newly designed as well as literature based primers for respective genus. A total 150 suspected meningitis CSF obtained from the patients admitted to Central India Institute of Medical Sciences (CIIMS), India during the period from August 2011 to May 2014, were used to evaluate clinical sensitivity and clinical specificity of optimized PCR assays. Results The analytical sensitivity and specificity of our newly designed genus-specific 16S rDNA PCR were found to be C92 %. With such a high sensitivity and specificity, our in-house nested PCR was able to give 100 % sensitivity in clinically confirmed positive cases and 100 % specificity in clinically confirmed negative cases indicating its applicability in clinical diagnosis

Differential Levels of Alpha-2-Macroglobulin, Haptoglobin and Sero-Transferrin as Adjunct Markers for TB Diagnosis and Disease Progression in the Malnourished Tribal Population of Melghat, India

<div><p>Lack of diagnostic capacity has been a crucial barrier preventing an effective response to the challenges of malnutrition and tuberculosis (TB). Point-of-care diagnostic tests for TB in immuno-incompetent, malnourished population are thus needed to ensure rapid and accurate detection. The aim of the study was to identify potential biomarkers specific for TB infection and progression to overt disease in the malnourished population of Melghat. A prospective cohort study was conducted in the year 2009 through 2011 in six villages of the Melghat region. 275 participants consisting of malnourished cases with a) active TB (n = 32), b) latent TB infection (n = 90), c) with no clinical or bacteriological signs of active or latent TB (n = 130) and healthy control subjects (n = 23) were recruited for the study. The proteome changes of the host serum in response to <i>Mycobacterium tuberculosis</i> (<i>M</i>.<i>tb</i>) infection were investigated using one dimensional electrophoresis in combination with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Three most differentially expressed proteins; alpha-2-macroglobulin (A-2-M), sero-transferrin and haptoglobin were identified by MALDI-TOF MS analysis, which were up-regulated in the malnourished patients with active TB and down-regulated in the malnourished patients compared with the healthy controls. Additionally, follow-up studies indicated that the expression of these proteins increased to nearly two folds in patients who developed active disease from latent state. Our preliminary results suggest that A-2-M, sero-transferrin and haptoglobin may be clinically relevant host biomarkers for TB diagnosis and disease progression in the malnourished population. This study provides preliminary framework for an in-depth analysis of the biomarkers in larger well-characterized cohorts. Evaluation of these biomarkers in follow-up cases may further aid in improving TB diagnosis.</p></div

Protein functions in tuberculosis and malnutrition.

<p>Table enlists the roles of the three identified proteins in malnutrition and tuberculosis reported in various studies.</p><p>Protein functions in tuberculosis and malnutrition.</p

Study participation diagram.

<p>The figure represents the inclusion/exclusion criteria adopted for recruitment of the study population. The population was categorized into four groups namely: Malnourished group with Active TB (n = 32), Malnourished group with Latent TB (n = 90), Malnourished group (n = 130) and Healthy control group (n = 23) (Grey boxes indicate the groups included in the final analysis). TB-Tuberculosis, TST-Tuberculin Skin Test, Cut-off point is atleast 10 mm, QFT- QuantiFERON-TB Gold, Cut-off is atleast 0.35 IU/μl. TLC-Total leukocyte count, Hb-Hemoglobin count (g/ml)</p

Expression of proteins by densitometric analysis.

<p>Pie charts represent the intensities of protein bands assessed by densitometric analysis in different study groups. Gel analysis was done using Image Lab software (BioRad) (Version 4.0)</p

Baseline characteristics of population under study.

<p>Characteristics of 275 subjects with the number of positive responders for each category are presented in the table. Percentages are indicated in parentheses. The statistical variance between groups was calculated using Chi squared test and p value. P < 0.05 was considered statistically significant. Statistical analysis was done using MedCalc statistical software (version 10.1.2.0).</p><p>Df, Degrees of freedom.</p><p>Baseline characteristics of population under study.</p

Representative 1-DE gel images of identified proteins in different categories.

<p>Boxes indicate the differentially expressed protein bands in different study groups. Gel imaging and analysis was done using Image Lab software (version 4.0, BioRad). The protein bands in the test groups were compared against healthy control group.</p