38 research outputs found
Genetic variability and consequence of Mycobacterium tuberculosis lineage 3 in Kampala-Uganda
Limited data existed exclusively describing Mycobacterium tuberculosis lineage 3 (MTB-L3), sub-lineages, and clinical manifestations in Kampala, Uganda. This study sought to elucidate the circulating MTB-L3 sub-lineages and their corresponding clinical phenotypes.; A total of 141 M. tuberculosis isolates were identified as M. tuberculosis lineage 3 using Single nucleotide polymorphism (SNP) marker analysis method. To ascertain the sub-lineages/sub-strains within the M. tuberculosis lineage 3, the direct repeat (DR) loci for all the isolates was examined for sub-lineage specific signatures as described in the SITVIT2 database. The infecting sub-strains were matched with patients' clinical and demographic characteristics to identify any possible association.; The data showed 3 sub-lineages circulating with CAS 1 Delhi accounting for 55% (77/141), followed by CAS 1-Kili 16% (22/141) and CAS 2/CAS 8% (12/141). Remaining isolates 21% (30/141) were unclassifiable. To explore whether the sub-lineages differ in their ability to cause increased severe disease, we used extent of lung involvement as a proxy for severe disease. Multivariable analysis showed no association between M. tuberculosis lineage 3 sub-lineages with severe disease. The risk factors associated with severe disease include having a positive smear (OR = 9.384; CI 95% = 2.603-33.835), HIV (OR = 0.316; CI 95% = 0.114-0.876), lymphadenitis (OR = 0. 171; CI 95% = 0.034-0.856) and a BCG scar (OR = 0.295; CI 95% = 0.102-0.854).; In Kampala, Uganda, there are three sub-lineages of M. tuberculosis lineage 3 that cause disease of comparable severity with CAS-Dehli as the most prevalent. Having HIV, lymphadenitis, a BCG scar and a smear negative status is associated with reduced severe disease
Clinical and epidemiological characteristics of individuals resistant to M. tuberculosis infection in a longitudinal TB household contact study in Kampala, Uganda
Genome Scan of M. tuberculosis Infection and Disease in Ugandans
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is an enduring public health problem globally, particularly in sub-Saharan Africa. Several studies have suggested a role for host genetic susceptibility in increased risk for TB but results across studies have been equivocal. As part of a household contact study of Mtb infection and disease in Kampala, Uganda, we have taken a unique approach to the study of genetic susceptibility to TB, by studying three phenotypes. First, we analyzed culture confirmed TB disease compared to latent Mtb infection (LTBI) or lack of Mtb infection. Second, we analyzed resistance to Mtb infection in the face of continuous exposure, defined by a persistently negative tuberculin skin test (PTST-); this outcome was contrasted to LTBI. Third, we analyzed an intermediate phenotype, tumor necrosis factor-alpha (TNFα) expression in response to soluble Mtb ligands enriched with molecules secreted from Mtb (culture filtrate). We conducted a full microsatellite genome scan, using genotypes generated by the Center for Medical Genetics at Marshfield. Multipoint model-free linkage analysis was conducted using an extension of the Haseman-Elston regression model that includes half sibling pairs, and HIV status was included as a covariate in the model. The analysis included 803 individuals from 193 pedigrees, comprising 258 full sibling pairs and 175 half sibling pairs. Suggestive linkage (p<10−3) was observed on chromosomes 2q21-2q24 and 5p13-5q22 for PTST-, and on chromosome 7p22-7p21 for TB; these findings for PTST- are novel and the chromosome 7 region contains the IL6 gene. In addition, we replicated recent linkage findings on chromosome 20q13 for TB (p = 0.002). We also observed linkage at the nominal α = 0.05 threshold to a number of promising candidate genes, SLC11A1 (PTST- p = 0.02), IL-1 complex (TB p = 0.01), IL12BR2 (TNFα p = 0.006), IL12A (TB p = 0.02) and IFNGR2 (TNFα p = 0.002). These results confirm not only that genetic factors influence the interaction between humans and Mtb but more importantly that they differ according to the outcome of that interaction: exposure but no infection, infection without progression to disease, or progression of infection to disease. Many of the genetic factors for each of these stages are part of the innate immune system
Infant BCG vaccination and risk of pulmonary and extrapulmonary tuberculosis throughout the life course: a systematic review and individual participant data meta-analysis.
BACKGROUND: BCG vaccines are given to more than 100 million children every year, but there is considerable debate regarding the effectiveness of BCG vaccination in preventing tuberculosis and death, particularly among older children and adults. We therefore aimed to investigate the age-specific impact of infant BCG vaccination on tuberculosis (pulmonary and extrapulmonary) development and mortality. METHODS: In this systematic review and individual participant data meta-analysis, we searched MEDLINE, Web of Science, BIOSIS, and Embase without language restrictions for case-contact cohort studies of tuberculosis contacts published between Jan 1, 1998, and April 7, 2018. Search terms included "mycobacterium tuberculosis", "TB", "tuberculosis", and "contact". We excluded cohort studies that did not provide information on BCG vaccination or were done in countries that did not recommend BCG vaccination at birth. Individual-level participant data for a prespecified list of variables, including the characteristics of the exposed participant (contact), the index case, and the environment, were requested from authors of all eligible studies. Our primary outcome was a composite of prevalent (diagnosed at or within 90 days of baseline) and incident (diagnosed more than 90 days after baseline) tuberculosis in contacts exposed to tuberculosis. Secondary outcomes were pulmonary tuberculosis, extrapulmonary tuberculosis, and mortality. We derived adjusted odds ratios (aORs) using mixed-effects, binary, multivariable logistic regression analyses with study-level random effects, adjusting for the variable of interest, baseline age, sex, previous tuberculosis, and whether data were collected prospectively or retrospectively. We stratified our results by contact age and Mycobacterium tuberculosis infection status. This study is registered with PROSPERO, CRD42020180512. FINDINGS: We identified 14 927 original records from our database searches. We included participant-level data from 26 cohort studies done in 17 countries in our meta-analysis. Among 68 552 participants, 1782 (2·6%) developed tuberculosis (1309 [2·6%] of 49 686 BCG-vaccinated participants vs 473 [2·5%] of 18 866 unvaccinated participants). The overall effectiveness of BCG vaccination against all tuberculosis was 18% (aOR 0·82, 95% CI 0·74-0·91). When stratified by age, BCG vaccination only significantly protected against all tuberculosis in children younger than 5 years (aOR 0·63, 95% CI 0·49-0·81). Among contacts with a positive tuberculin skin test or IFNγ release assay, BCG vaccination significantly protected against tuberculosis among all participants (aOR 0·81, 95% CI 0·69-0·96), participants younger than 5 years (0·68, 0·47-0·97), and participants aged 5-9 years (0·62, 0·38-0·99). There was no protective effect among those with negative tests, unless they were younger than 5 years (0·54, 0·32-0·90). 14 cohorts reported on whether tuberculosis was pulmonary or extrapulmonary (n=57 421). BCG vaccination significantly protected against pulmonary tuberculosis among all participants (916 [2·2%] in 41 119 vaccinated participants vs 334 [2·1%] in 16 161 unvaccinated participants; aOR 0·81, 0·70-0·94) but not against extrapulmonary tuberculosis (106 [0·3%] in 40 318 vaccinated participants vs 38 [0·2%] in 15 865 unvaccinated participants; 0·96, 0·65-1·41). In the four studies with mortality data, BCG vaccination was significantly protective against death (0·25, 0·13-0·49). INTERPRETATION: Our results suggest that BCG vaccination at birth is effective at preventing tuberculosis in young children but is ineffective in adolescents and adults. Immunoprotection therefore needs to be boosted in older populations. FUNDING: National Institutes of Health
Impact of geographic distance on appraisal delay for active TB treatment seeking in Uganda: a network analysis of the Kawempe Community Health Cohort Study
Abstract Background Appraisal delay is the time a patient takes to consider a symptom as not only noticeable, but a sign of illness. The study’s objective was to determine the association between appraisal delay in seeking tuberculosis (TB) treatment and geographic distance measured by network travel (driving and pedestrian) time (in minutes) and distance (Euclidean and self-reported) (in kilometers) and to identify other risk factors from selected covariates and how they modify the core association between delay and distance. Methods This was part of a longitudinal cohort study known as the Kawempe Community Health Study based in Kampala, Uganda. The study enrolled households from April 2002 to July 2012. Multivariable interval regression with multiplicative heteroscedasticity was used to assess the impact of time and distance on delay. The delay interval outcome was defined using a comprehensive set of 28 possible self-reported symptoms. The main independent variables were network travel time (in minutes) and Euclidean distance (in kilometers). Other covariates were organized according to the Andersen utilization conceptual framework. Results A total of 838 patients with both distance and delay data were included in the network analysis. Bivariate analyses did not reveal a significant association of any distance metric with the delay outcome. However, adjusting for patient characteristics and cavitary disease status, the multivariable model indicated that each minute of driving time to the clinic significantly (p = 0.02) and positively predicted 0.25 days’ delay. At the median distance value of 47 min, this represented an additional delay of about 12 (95% CI: [3, 21]) days to the mean of 40 days (95% CI: [25, 56]). Increasing Euclidean distance significantly predicted (p = 0.02) reduced variance in the delay outcome, thereby increasing precision of the mean delay estimate. At the median Euclidean distance of 2.8 km, the variance in the delay was reduced by more than 25%. Conclusion Of the four geographic distance measures, network travel driving time was a better and more robust predictor of mean delay in this setting. Including network travel driving time with other risk factors may be important in identifying populations especially vulnerable to delay
Impact of geographic distance on appraisal delay for active TB treatment seeking in Uganda: a network analysis of the Kawempe Community Health Cohort Study
The study’s objective was to determine the association between appraisal delay in seeking tuberculosis
(TB) treatment and geographic distance measured by network travel (driving and pedestrian) time (in minutes) and
distance (Euclidean and self-reported) (in kilometers) and to identify other risk factors from selected covariates and
how they modify the core association between delay and distance.Background: Appraisal delay is the time a patient takes to consider a symptom as not only noticeable, but a sign
of illness. The study’s objective was to determine the association between appraisal delay in seeking tuberculosis
(TB) treatment and geographic distance measured by network travel (driving and pedestrian) time (in minutes) and distance (Euclidean and self-reported) (in kilometers) and to identify other risk factors from selected covariates and how they modify the core association between delay and distance.
Methods: This was part of a longitudinal cohort study known as the Kawempe Community Health Study based in
Kampala, Uganda. The study enrolled households from April 2002 to July 2012. Multivariable interval regression with multiplicative heteroscedasticity was used to assess the impact of time and distance on delay. The delay interval outcome was defined using a comprehensive set of 28 possible self-reported symptoms. The main independent variables were network travel time (in minutes) and Euclidean distance (in kilometers). Other covariates were organized according to the Andersen utilization conceptual framework.
Results: A total of 838 patients with both distance and delay data were included in the network analysis. Bivariate
analyses did not reveal a significant association of any distance metric with the delay outcome. However, adjusting for patient characteristics and cavitary disease status, the multivariable model indicated that each minute of driving time to the clinic significantly (p = 0.02) and positively predicted 0.25 days’ delay. At the median distance value of 47 min, this represented an additional delay of about 12 (95% CI: [3, 21]) days to the mean of 40 days (95% CI: [25, 56]). Increasing Euclidean distance significantly predicted (p = 0.02) reduced variance in the delay outcome, thereby increasing precision of the mean delay estimate. At the median Euclidean distance of 2.8 km, the variance in the delay was reduced by more than 25%.
Conclusion: Of the four geographic distance measures, network travel driving time was a better and more robust
predictor of mean delay in this setting. Including network travel driving time with other risk factors may be
important in identifying populations especially vulnerable to delay
Tuberculosis severity associates with variants and eQTLs related to vascular biology and infection-induced inflammation.
BackgroundTuberculosis (TB) remains a major public health problem globally, even compared to COVID-19. Genome-wide studies have failed to discover genes that explain a large proportion of genetic risk for adult pulmonary TB, and even fewer have examined genetic factors underlying TB severity, an intermediate trait impacting disease experience, quality of life, and risk of mortality. No prior severity analyses used a genome-wide approach.Methods and findingsAs part of our ongoing household contact study in Kampala, Uganda, we conducted a genome-wide association study (GWAS) of TB severity measured by TBScore, in two independent cohorts of culture-confirmed adult TB cases (n = 149 and n = 179). We identified 3 SNPs (PConclusionsThese analyses reveal new insights into the genetics of TB severity with regulation of platelet homeostasis and vascular biology being central to consequences for active TB patients. This analysis also reveals genes that regulate inflammation can lead to differences in severity. Our findings provide an important step in improving TB patient outcomes
Clinical and epidemiological characteristics of individuals resistant to M. tuberculosis infection in a longitudinal TB household contact study in Kampala, Uganda
his is the first study to rigorously characterize the epidemiologic risk profile of individuals with persistently negative TSTs despite close exposure to a person with TB. Additional studies are needed to characterize possible epidemiologic and host factors associated with this phenotype.Background
Despite sustained exposure to a person with pulmonary tuberculosis (TB), some M. tuberculosis (Mtb) exposed individuals maintain a negative tuberculin skin test (TST). Our objective was to characterize these persistently negative TST (PTST-) individuals and compare them to TST converters (TSTC) and individuals who are TST positive at study enrollment.
Methods
During a TB household contact study in Kampala, Uganda, PTST-, TSTC, and TST + individuals were identified. PTST- individuals maintained a negative TST over a 2 year observation period despite prolonged exposure to an infectious tuberculosis (TB) case. Epidemiological and clinical characteristics were compared, a risk score developed by another group to capture risk for Mtb infection was computed, and an ordinal regression was performed.
Results
When analyzed independently, epidemiological risk factors increased in prevalence from PTST- to TSTC to TST+. An ordinal regression model suggested age (p < 0.01), number of windows (p < 0.01) and people (p = 0.07) in the home, and sleeping in the same room (p < 0.01) were associated with PTST- and TSTC. As these factors do not exist in isolation, we examined a risk score, which reflects an accumulation of risk factors. This compound exposure score did not differ significantly between PTST-, TSTC, and TST+, except for the 5–15 age group (p = 0.009).
Conclusions
Though many individual factors differed across all three groups, an exposure risk score reflecting a collection of risk factors did not differ for PTST-, TSTC and TST + young children and adults. This is the first study to rigorously characterize the epidemiologic risk profile of individuals with persistently negative TSTs despite close exposure to a person with TB. Additional studies are needed to characterize possible epidemiologic and host factors associated with this phenotype
Identification of Host Proteins Predictive of Early Stage Mycobacterium tuberculosis Infection
The objective of this study was to identify blood-based protein biomarkers of early stage Mycobacterium tuberculosis (Mtb) infection. We utilized plasma and serum specimens from TB patients and their contacts (age ≥ 12) enrolled in a household contact study in Uganda. In the discovery phase cross-sectional samples from 104 HIV-uninfected persons classified as either active TB, latent Mtb infection (LTBI), tuberculin skin test (TST) converters, or persistent TST-negative were analyzed. Two hundred eighty-nine statistically significant (false discovery rate corrected p  0.85. Panel performance was confirmed with an independent validation set of longitudinal samples from 16 subjects. These candidate protein biomarkers may allow for the identification of recently Mtb infected individuals at highest risk for developing active TB and most likely to benefit from preventive therapy
Epidemiologic Measures of TB exposure burden.
<p>Epidemiologic Measures of TB exposure burden.</p