44 research outputs found
Detection of mycobacterium tuberculosis complex DNA in CD34 positive versus CD34-Negative peripheral blood mononuclear cells and the determinants of IGRA positivity in latent Tuberculosis
No full textA thesis submitted to the Directorate of Research and Graduate Training in partial fulfillment of the award of Doctor of Philosophy of Makerere University.Background
Tuberculin skin test (TST) and interferon gamma release assay (IGRA), currently used to diagnose latent
tuberculosis infection (LTBI) have low positive predictive values for progression to active tuberculosis
(TB). We explored the detection of Mycobacterium tuberculosis complex (MTBC) DNA in peripheral
blood mononuclear cells (PBMC) in the diagnosis of LTBI and monitoring response to isoniazid preventive
therapy (IPT).
Methodology
In a cross-sectional study (study 1), 121 close contacts of index pulmonary TB patients (59 HIV-negative
and 62 HIV-positive) were recruited to evaluate whether MTBC DNA was detectable in CD34-positive
versus CD34-negative PBMC of the close contacts. The close contacts each donated 100 milliliters (ml) of
whole blood for isolating PBMC using density gradient centrifugation and 4 ml for IGRA testing using the
QuantiFERON-TB Gold Plus assay (QFT-Plus). The PBMC were sorted into CD34-positive and CD34-
negative fractions using magnetic activated cell sorting. The hexadecyltrimethylammonium bromide
(CTAB) protocol was used to extract the PBMC DNA, from which MTBC DNA was then quantified using
droplet digital polymerase chain reaction (dPCR), targeting the MTBC-specific genes IS6110 and rpoB. In
a nested prospective study (study 2), the 62 HIV-infected participants in study one were given IPT for six
months to evaluate whether IPT reduced the proportion with detectable MTBC DNA and the number of
MTBC DNA copies in the CD34-positive and CD34-negative PBMC. The assays described above to detect
MTBC DNA were repeated at the end of six-month of IPT. In another cross sectional study (study 3), 289
close contacts of index pulmonary TB patients were recruited to determine their IGRA status and the
associated socio-demographic and clinical characteristics.
In descriptive analysis, the continuous predictor variables were reported as means with the standard
deviation and the categorical variables as proportions in terms of frequencies and percentages. For the
outcome variable (MTBC DNA copies), the median and interquartile range were used due presence of
outliers. In inferential analysis for studies one and two, the Fisher's exact test was used to compare the
proportions with detected MTBC DNA in the different categories of the predictor variables. The analysis
was performed with Stata/IC 15.0, StataCorp LLC Texas USA. The Wilcoxon signed rank test was used to
compare MTBC DNA copies for matched samples and the Mann Whitney U test for independent samples.
MacNemars test was used to determine the number of pairs with the outcome at baseline and follow-up.
The analysis was performed with GraphPad Prism 9.1. In study three, the random effect logistic regression
analysis was used to determine the factors associated with a positive IGRA test at both bivariate and
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multivariate logistic regression analysis. The analysis was performed with Stata/IC 15.0, StataCorp LLC
Texas USA. At all levels of comparison, the level of significance was a two tailed P-value < 0.05.
Study results In study one, MTBC DNA was detected in PBMC of 106/119 (89%, 95% CI 0.82-0.94) participants. There
were more participants in whom MTBC DNA was detected in CD34+ vs CD34-negative PBMC (103/119
[87%] vs 59/119 [50%]; p=0.007). More participants had IS6110 detected than rpoB in both CD34-negative
PBMC (57/119 [48%] vs 38/119 [32%]; p<0·0001) and CD34-positive PBMC (101/119 [85%] vs 80/119
[67%]; p<0·0001). The median IS6110 copy number in CD34-negtive PBMC was 0.0 (IQR: 0.0 - 666.7)
copies/hDNA and 825.0 (IQR: 166.7 - 56601.9) copies/hDNA in CD34-positive PBMC while the median
rpoB copy number in CD34-negative PBMC was 0.0 (IQR: 0.0 – 50.0) copies/hDNA and 120.7 (IQR: 0.0 - 4859.1) in the CD34-positive PBMC.
The proportion of participants in whom MTBC DNA was detected in PBMC did not differ between QFT
negative vs QFT-positive individuals (56/113 [50%] vs 57/113 [50%]; p=0·51). The IS6110 copies did not
also differ according to QFT status in either CD34-positive or CD34-negative PBMC. The CD34-negative
PBMC in the QFT-negative had a median IS6110 copy number of 0.0 (IQR: 0.0 - 664.4) vs. 0.0 (IQR: 0.0 - 310.0) copies/hDNA in QFT-positive. The CD34-positive PBMC in the QFT-negative had a median
IS6110 copy number of 1361.1 (IQR: 220.0 - 129315.1) vs. 537.6 (IQR: 115.0 - 3406.4) copies/hDNA in
the QFT-positive. However, more rpoB copies were found in QFT-negative compared to QFT-positive
individuals (P=0.03) in the CD34-positive PBMC [356.9 (IQR: 0.0 - 10609.3) vs. 53.0 (IQR: 0.0 - 400.0)
copies/hDNA] unlike in the CD34-negative PBMC [0.0 (IQR 0.0 - 38.2) copies/hDNA vs. 0.0 (IQR: 0.0 -
34.0) copies/hDNA]. On the other hand, the proportions with detectable MTBC DNA did not differ between HIV-infected vs.
HIV-uninfected participants (56/119 (47%) vs 50/119 (42%), p=0·44). Likewise, the IS6110 and the rpoB
DNA copies did not differ according to HIV status, in either the CD34-positive or CD34-negative PBMC.
The CD34-negative PBMC in HIV-negative had a median IS6110 copy number of 0.0 (IQR: 0.0 - 980.6)
vs. 0.0 (IQR: 0.0 - 270.0) copies/hDNA in the HIV-positive while the CD34-positive PBMC had a median
IS6110 copy number of 1050.0 (IQR: 166.7 - 130000.0) vs. 650.0 (IQR: 172.2 - 28500.0) copies/hDNA
respectively. Similarly, the CD34-negative PBMC in HIV-negative had a median rpoB copy number of 0.0
(IQR: 0.0 - 63.2) vs. 0.0 (IQR: 0.0 – 34.0) copies/hDNA in the HIV-positive while the CD34-positive
PBMC had a median rpoB copy numbers of 123.7 (IQR: 0.0 - 1903.0) vs. 117.6 (IQR: 0.0 - 3150.0)
copies/hDNA respectively. In study two, the proportion with detectable IS6110 copies did not differ between baseline and follow:
CD34-negative, 25/53 vs. 27/53 (p=0.448) and CD34-positive: 43/53 vs. 46/53(P=0.520). Likewise, the
proportions didn’t differ for rpoB: CD34-negative, 36/53 vs. 41/53 (P=0.214) and CD34-positive: 13/53 vs.
25/53 (P=0.345) respectively. Similarly, the baseline and post-IPT IS6110 and rpoB copies were not
different. The CD34-negative PBMC at baseline had a median IS6110 copy number of 0.0 (IQR: 0.0 -
270.0) vs. 21.4 (IQR: 0.0 - 245.1) copies/hDNA post-IPT while the CD34-positive PBMC had a median
IS6110 copy number of 650.0 (IQR: 172.2 - 28500.0) vs. 1179.0 (IQR: 225.0 - 6050.0) copies/hDNA
respectively. The CD34-negative PBMC at baseline had a median rpoB copy number of 0.0 (IQR: 0.0 -
34.0) vs. 0.0 (IQR: 0.0 - 97.8) copies/hDNA post-IPT while the CD34-positive PBMC had a median rpoB
copy number of 117.6 (IQR: 0.0 - 3150.0) vs. 181.3 (IQR: 17.4 - 521.7) copies/hDNA respectively.
In study three, overall, 105/192 (54%, 95% CI 0.48-0.62) participants had a positive QFT Plus result. The
risk of QFT-Plus positivity was independently associated with casual employment/unemployment vs. non
casual employment (adjusted odds ratio (aOR) 2.18, 95% CI 1.01-4.72), family vs. non-family relation to
the index patient (aOR 2.87, 95% CI 1.33-6.18), living in the same vs. a different house as the index (aOR
3.05, 95% CI 1.28-7.29), a higher body mass index (BMI) (aOR per additional kg/m2 1.09, 95% CI 1.00
1.18) and tobacco smoking vs. not smoking (aOR 2.94, 95% CI 1.00-8.60). HIV infection was not
associated with QFT-Plus positivity (aOR 0.91, 95% CI 0.42-1.96).
Conclusion
Mycobacterium tuberculosis complex DNA was detected in PBMC, and the copy number and frequency of
detection were higher in the CD34-postive vs. CD34-negative fraction, making PBMC a potential niche for
MTBC during latent TB. Isoniazid preventive therapy did not decrease the frequency of MTBC DNA
detection nor the copy numbers. IGRA positivity was associated with manual employment, closer contact with the index case, tobacco smoking and increment in BMI.
Recommendations 1. Before detection of M. tuberculosis DNA in PBMC can be adopted as a molecular test for latent TB
infection, prospective studies are required to determine whether a positive test associates with increased
risk of progression to active TB.
2. The above determinant of IGRA positivity may be utilized in identifying groups at risk of latent TB,
which need to be targeted for screening
Detection of Mycobacterium tuberculosis DNA in CD34+ peripheral blood mononuclear cells of Ugandan adults with latent infection: A cross-sectional & nested prospective study
No full textLTBI diagnosis stud
Utility of the monocyte to lymphocyte ratio in diagnosing latent tuberculosis among HIV-infected individuals with a negative tuberculosis symptom screen.
No full textBackgroundLatent Tuberculosis Infection (LTBI) remains a major driver of the TB epidemic, and individuals with Human Immuno-deficiency Virus (HIV) are particularly at a heightened risk of developing LTBI. However, LTBI screening among HIV-infected individuals in resource limited setting is largely based on a negative symptom screen, which has low specificity.MethodsIn a cross sectional diagnostic study, 115 HIV infected participants with a negative symptom screen will be consented and enrolled. They will be requested to donate 5 ml of blood for complete blood count (CBC) and interferon gamma release assay (IGRA) testing. In a nested prospective study, the 115 participants will be initiated on Tuberculosis Preventive Therapy and the CBC testing repeated after 3 months. In the analysis of study finding, the monocyte to lymphocyte ratio (MLR) will be derived from the dividend of the absolute monocyte and lymphocyte counts. The optimal MLR positivity cut-off for elevated or normal MLR will be the highest value of Youden's index, J (sensitivity + specificity-1). The MLR will be cross tabulated with the IGRA status to determine the sensitivity, specificity, negative and positive predictive values of the MLR. The area under the receiver operating characteristic (ROC) curve will be determined to give the overall diagnostic accuracy of MLR. The baseline and 3 month CBC will be used to determine the change in MLR, and a random effect logistic regression will be used to determine factors associated with the change in the MLR.DiscussionIf positive results are realized from this study, the MLR could become an inexpensive alternative biomarker with potential to improve the specificity of the negative symptom screen in identifying individuals that should be targeted for TB preventive therapy
Monocyte to Lymphocyte ratio is highly specific in diagnosing latent tuberculosis and declines significantly following tuberculosis preventive therapy: A cross-sectional and nested prospective observational study.
No full textBackgroundInterferon-gamma release assay and tuberculin skin test use is limited by costly sundries and cross-reactivity with non-tuberculous mycobacteria and Bacille Calmette-Guérin (BCG) vaccination respectively. We investigated the Monocyte to Lymphocyte ratio (MLR) as a biomarker to overcome these limitations and for use in monitoring response to tuberculosis preventive therapy (TPT).MethodsWe conducted a cross-sectional and nested prospective observational study among asymptomatic adults living with Human Immuno-deficiency Virus (HIV) in Kampala, Uganda. Complete blood count (CBC) and QuantiFERON-TB® Gold-plus were measured at baseline and CBC repeated at three months. Multivariable logistic regression was performed to identify factors associated with a high MLR and decline in MLR.ResultsWe recruited 110 adults living with HIV and on antiretroviral therapy, of which 82.5% (85/110) had suppressed viral loads, 71.8% (79/110) were female, and 73.6% (81/110) had a BCG scar. The derived MLR diagnostic cut-off was 0.35, based on which the MLR sensitivity, specificity, positive predictive value, and negative predictive value were 12.8%, 91.6%, 45.5%, and 65.7% respectively. The average MLR declined from 0.212 (95% CI: 0.190-0.235) at baseline to 0.182 (95% CI: 0.166-0.198) after three months of TPT. A viral load of >50 copies/ml (aOR, 5.67 [1.12-28.60]) was associated with a high MLR while that of ConclusionMLR was highly specific in diagnosing latent TB and declined significantly following three months of TPT. Implications of a high MLR and decline in MLR after TPT need further evaluation in a larger cohort
Angiotensin II status and sympathetic activation among hypertensive patients in Uganda: a cross-sectional study
No full textAccuracy of anti-mycobacterial protein 51 antibodies as a biomarker for latent TB infection in asymptomatic HIV positive individuals: a cross-sectional diagnostic study
No full textAbstract Objective To evaluate the diagnostic accuracy of anti-Mycobacterial Protein 51 (MPT51) antibodies in latent Tuberculosis (TB) detection among asymptomatic Human Immune Virus (HIV) positive individuals using Interferon Gamma Release Assay (IGRA) (QuantiFERON-TB Gold Plus) as the gold standard and determine the factors associated with anti-MPT51 antibody positivity among asymptomatic HIV positive individuals. Results Considering QuantiFERON-TB Gold Plus as the gold standard, antibody reactivity to MPT51 revealed sensitivity of 32.6% (95% CI 24.5–40.6), specificity of 56.1% (95% CI 47.6–64.6), positive predictive value of 61.7% (95% CI 53.4–70.1) and negative predictive value of 27.7% (95% CI 20-35.4). Among the factors tested, none was independently associated with an increased risk of antibody reactivity against MPT51
Factors associated with a decline in MLR.
No full textBackgroundInterferon-gamma release assay and tuberculin skin test use is limited by costly sundries and cross-reactivity with non-tuberculous mycobacteria and Bacille Calmette-Guérin (BCG) vaccination respectively. We investigated the Monocyte to Lymphocyte ratio (MLR) as a biomarker to overcome these limitations and for use in monitoring response to tuberculosis preventive therapy (TPT).MethodsWe conducted a cross-sectional and nested prospective observational study among asymptomatic adults living with Human Immuno-deficiency Virus (HIV) in Kampala, Uganda. Complete blood count (CBC) and QuantiFERON-TB® Gold-plus were measured at baseline and CBC repeated at three months. Multivariable logistic regression was performed to identify factors associated with a high MLR and decline in MLR.ResultsWe recruited 110 adults living with HIV and on antiretroviral therapy, of which 82.5% (85/110) had suppressed viral loads, 71.8% (79/110) were female, and 73.6% (81/110) had a BCG scar. The derived MLR diagnostic cut-off was 0.35, based on which the MLR sensitivity, specificity, positive predictive value, and negative predictive value were 12.8%, 91.6%, 45.5%, and 65.7% respectively. The average MLR declined from 0.212 (95% CI: 0.190–0.235) at baseline to 0.182 (95% CI: 0.166–0.198) after three months of TPT. A viral load of >50 copies/ml (aOR, 5.67 [1.12–28.60]) was associated with a high MLR while that of ConclusionMLR was highly specific in diagnosing latent TB and declined significantly following three months of TPT. Implications of a high MLR and decline in MLR after TPT need further evaluation in a larger cohort.</div
Angiotensin II status and sympathetic activation among hypertensive patients in Uganda: a cross-sectional study
No full text<p>A cross sectional study conducted at Mulago, the national referral hospital. Blood samples were taken to measure angiotensin II, metanephrines, normetanephrines and urine samples for creatinine and sodium. The angiotensin II categories were defined using the Mosby's Diagnostic and Laboratory Test References. 9th ed while the metanephrines and normetanephrine cartegories were defined using the Makerere University Biosafety II Immunology Laboratory reference values.</p>
The receiver operative curve for the diagnostic utility of MLR.
No full textThe receiver operative curve for the diagnostic utility of MLR.</p
A Systems Approach to Monitoring Antimicrobial Consumption and Use in Uganda
No full textIntroduction: The Antimicrobial resistance (AMR) threat necessitates coordinated and complementary systems to effectively monitor antimicrobial consumption and use (AMUC). The current approaches to standardize data collection don't capture the complexities of AMUC patterns and the diverse influencing factors. We present Uganda's experience in the adoption of the six building blocks of the WHO Health System Framework in monitoring AMUC. Methods: Uganda's approach recognizes that AMUC is influenced by healthcare delivery, governance structures, financing mechanisms, workforce capacity, and information systems. Furthermore, it acknowledges the critical role of supply chain for essential medicines in shaping AMUC patterns. Uganda, therefore, instituted an approach that integrates data from multiple sources, such as imports, distribution and individual patient use for a comprehensive understanding of AMUC dynamics. The leadership, governance structures and coordination mechanisms were defined; and their roles and responsibilities anchored in policies to improve appropriate AMUC. Continuous quality improvement (CQI) policies ensure use of the data for effective use of resources in averting consequences of AMR. Results: Ministry of Health (MoH) established an advisory group on appropriate medicine use that works collaboratively with other national structures to guide on the availability and appropriate use of antimicrobials. A national policy to ensure the implementation of antimicrobial stewardship at facilities has fostered the appointment and functionalizing of multidisciplinary medicines and therapeutic committees in health facilities. These policy frameworks have created budget lines and opportunities to prioritize the interventions that improve antibiotic use. This policy and the national guidelines for monitoring AMUC have enabled health facilities to conduct regular antimicrobial use surveys. Through continuous training and support supervision, MoH has also built capacity for data storage, analysis and use for CQI. MoH has been able to generate consumption data contributing to global databases such as WHO GLASS as well as contextualize the extent of the burden of irrational use of antibiotics. Finally, interdisciplinary collaboration has ensured involvement of stakeholders at national, facility and community levels. Discussion: By adopting a systems approach, Uganda has enhanced the accuracy, relevance, and sustainability of surveillance and optimal use of antimicrobials. Understanding the complex interactions between various stakeholders, policies, and practices has informed evidence-based interventions to mitigate AMR. Conclusion: A systems approach fosters a holistic understanding of the dynamics of AMUC, which contributes to building resilient health systems capable of effectively addressing emerging health threats
