Browsing by Author "Maasdorp, Elizna"
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- ItemCombining different types of highly parallelised technology datasets for bioinformatic analysis in the context of biomarker discovery for tuberculosis disease and treatment response(Stellenbosch : Stellenbosch University, 2021-12) Maasdorp, Elizna; Tromp, G. C.; Walzl, G.; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Biomedical Sciences: Molecular Biology and Human Genetics.Background: Monitoring of tuberculosis (TB) treatment response currently relies on month 2 sputum culture. It is a poor predictor of ultimate treatment failure and recurrent disease and has a long turnaround time of up to six weeks. A biomarker of treatment response to identify patients at high risk of poor outcomes will benefit both TB patient care and TB research. It has been shown that patients with negative end-of-treatment sputum culture can still have a highly inflammatory picture on Positron Emission Tomography and Computerised Tomography (PET-CT) scans at the same time point. This inflammation may be in response to the presence of viable Mycobacterium tuberculosis bacilli which were not sampled in sputum, or not culturable, or it may be due to ongoing immune dysregulation, which is a well-known phenomenon in TB. Currently, we are not able to distinguish between these potential scenarios, but despite this, it is clear that PET-CT provides complementary information to microbiology at the end of treatment. Since PET-CT is expensive and not widely available, it would be most practical to obtain similar information to what PET-CT provides, from a blood-based biomarker. Several whole blood gene expression signatures have been discovered for diagnosis of active TB and sub-clinical disease, but none have yet attained to the World Health Organisation’s target product profiles for new diagnostic tests for TB. Gene expression signatures have also been investigated as biomarkers of treatment response, but none has been validated, as treatment response studies require many participants and long follow-up times, leading to a scarcity of adequate treatment response data sets. Objective To utilise treatment outcome groups derived from end-of-treatment PET-CT scans, as an alternative dependent variable to microbiological treatment outcome groups in predictive modelling, and to discover whether PET-CT could be replaced by multiplexed immunoassay data, gene expression data, or both in combination. Methods Two existing treatment response data sets were utilised – one from a study with follow-up during TB treatment until 2 years after treatment completion, and one early bactericidal activity study with two- week follow-up. Both studies produced PET-CT and multiplexed immunoassay (Luminex) data, while the longer study, which was the main focus of this thesis, additionally included gene expression data. Unsupervised hierarchical clustering of selected quantitative PET-CT variables at end-of-treatment was performed to create two outcome groups, independent of microbiological results, for predictive modelling. RNA-sequencing data and Luminex data at three time points, for the same cohort of patients, were used to predict membership of the PET-CT outcome groups, both separately and in combined models. Immunoassay data were also used in predictive regression models to explain a proportion of the variance in quantitative PET-CT variables. Results Two clusters of patients were identified from the PET-CT variables – one consisting of 23 participants with a predominantly inflammatory ("hot") lung picture, including seven of eight participants who failed treatment, and the second consisting of 76 participants with a less inflammatory or even resolved lung picture ("cold"). Both gene expression and Luminex data models could predict cluster membership and achieved cross-validation classification areas-under-the-curve (AUCs) that ranged from 0.74 to 0.90 at end-of-treatment. The models also achieved similar AUCs at the diagnosis time point. Combining gene expression and Luminex data in classification models did not improve on the classification accuracy of the separate models. Luminex analyte regression models explained 55% of the variance of the total glycolytic activity index PET-CT variable in a test and a validation set. A Luminex analyte classification model could also identify presence of cavities 1 mm or larger, with AUCs of 0.83 and 0.75 in the test and validation sets, respectively. Differential gene expression, gene ontology, pathway and weighted gene co-expression analysis focusing on the two PET-CT clusters, highlighted known immunological and TB-related processes that differed between the clusters and provided justification for using treatment outcome groups based on PET-CT, as a complementary strategy to using microbiological treatment outcome groups. Conclusion At the end of TB treatment, PET-CT provides complementary information to microbiological treatment outcomes, that could be utilised in specific scenarios in future studies to monitor treatment response. As PET-CT is expensive and not widely available, it is highly desirable to replace it with a biomarker measured in peripheral blood. I showed that gene expression or protein measured in peripheral blood could potentially replace PET-CT, but discovery of such a biomarker will benefit from a study designed for that purpose, and the availability of independent data sets for validation.
- ItemCombining different types of highly parallelised technology datasets for bioinformatic analysis in the context of biomarker discovery for tuberculosis disease and treatment response(Stellenbosch : Stellenbosch University, 2021-03) Maasdorp, Elizna; Tromp, G. C.; Walzl, G.; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Biomedical Sciences: Molecular Biology and Human Genetics.Background: Monitoring of tuberculosis (TB) treatment response currently relies on month 2 sputum culture. It is a poor predictor of ultimate treatment failure and recurrent disease and has a long turnaround time of up to six weeks. A biomarker of treatment response to identify patients at high risk of poor outcomes will benefit both TB patient care and TB research. It has been shown that patients with negative end-of-treatment sputum culture can still have a highly inflammatory picture on Positron Emission Tomography and Computerised Tomography (PET-CT) scans at the same time point. This inflammation may be in response to the presence of viable Mycobacterium tuberculosis bacilli which were not sampled in sputum, or not culturable, or it may be due to ongoing immune dysregulation, which is a well-known phenomenon in TB. Currently, we are not able to distinguish between these potential scenarios, but despite this, it is clear that PET-CT provides complementary information to microbiology at the end of treatment. Since PET-CT is expensive and not widely available, it would be most practical to obtain similar information to what PET-CT provides, from a blood-based biomarker. Several whole blood gene expression signatures have been discovered for diagnosis of active TB and sub-clinical disease, but none have yet attained to the World Health Organisation’s target product profiles for new diagnostic tests for TB. Gene expression signatures have also been investigated as biomarkers of treatment response, but none has been validated, as treatment response studies require many participants and long follow-up times, leading to a scarcity of adequate treatment response data sets. Objective To utilise treatment outcome groups derived from end-of-treatment PET-CT scans, as an alternative dependent variable to microbiological treatment outcome groups in predictive modelling, and to discover whether PET-CT could be replaced by multiplexed immunoassay data, gene expression data, or both in combination. Methods Two existing treatment response data sets were utilised – one from a study with follow-up during TB treatment until 2 years after treatment completion, and one early bactericidal activity study with twoweek follow-up. Both studies produced PET-CT and multiplexed immunoassay (Luminex) data, while the longer study, which was the main focus of this thesis, additionally included gene expression data. Unsupervised hierarchical clustering of selected quantitative PET-CT variables at end-of-treatment was performed to create two outcome groups, independent of microbiological results, for predictive modelling. RNA-sequencing data and Luminex data at three time points, for the same cohort of patients, were used to predict membership of the PET-CT outcome groups, both separately and in combined models. Immunoassay data were also used in predictive regression models to explain a proportion of the variance in quantitative PET-CT variables. Results Two clusters of patients were identified from the PET-CT variables – one consisting of 23 participants with a predominantly inflammatory ("hot") lung picture, including seven of eight participants who failed treatment, and the second consisting of 76 participants with a less inflammatory or even resolved lung picture ("cold"). Both gene expression and Luminex data models could predict cluster membership and achieved cross-validation classification areas-under-the-curve (AUCs) that ranged from 0.74 to 0.90 at end-of-treatment. The models also achieved similar AUCs at the diagnosis time point. Combining gene expression and Luminex data in classification models did not improve on the classification accuracy of the separate models. Luminex analyte regression models explained 55% of the variance of the total glycolytic activity index PET-CT variable in a test and a validation set. A Luminex analyte classification model could also identify presence of cavities 1 mm or larger, with AUCs of 0.83 and 0.75 in the test and validation sets, respectively. Differential gene expression, gene ontology, pathway and weighted gene co-expression analysis focusing on the two PET-CT clusters, highlighted known immunological and TB-related processes that differed between the clusters and provided justification for using treatment outcome groups based on PET-CT, as a complementary strategy to using microbiological treatment outcome groups. Conclusion At the end of TB treatment, PET-CT provides complementary information to microbiological treatment outcomes, that could be utilised in specific scenarios in future studies to monitor treatment response. As PET-CT is expensive and not widely available, it is highly desirable to replace it with a biomarker measured in peripheral blood. I showed that gene expression or protein measured in peripheral blood could potentially replace PET-CT, but discovery of such a biomarker will benefit from a study designed for that purpose, and the availability of independent data sets for validation.
- ItemDiagnostic potential of novel salivary host biomarkers as candidates for the immunological diagnosis of tuberculosis disease and monitoring of tuberculosis treatment response(Public Library of Science, 2016-08-03) Jacobs, Ruschca; Maasdorp, Elizna; Malherbe, Stephanus; Loxton, Andre G.; Stanley, Kim; Van Der Spuy, Gian; Walzl, Gerhard; Chegou, Novel N.Background: There is an urgent need for new tools for the early diagnosis of TB disease and monitoring of the response to treatment, especially in resource-constrained settings. We investigated the usefulness of host markers detected in saliva as candidate biomarkers for the immunological diagnosis of TB disease and monitoring of treatment response. Methods: We prospectively collected saliva samples from 51 individuals that presented with signs and symptoms suggestive of TB disease at a health centre in Cape Town, South Africa, prior to the establishment of a clinical diagnosis. Patients were later classified as having TB disease or other respiratory disease (ORD), using a combination of clinical, radiological and laboratory findings. We evaluated the concentrations of 69 host markers in saliva samples using a multiplex cytokine platform, and assessed the diagnostic potentials of these markers by receiver operator characteristics (ROC) curve analysis, and general discriminant analysis. Results: Out of the 51 study participants, 18 (35.4%) were diagnosed with TB disease and 12 (23.5%) were HIV infected. Only two of the 69 host markers that were evaluated (IL-16 and IL-23) diagnosed TB disease individually with area under the ROC curve ≥0.70. A five-marker biosignature comprising of IL-1β, IL-23, ECM-1, HCC1 and fibrinogen diagnosed TB disease with a sensitivity of 88.9% (95% CI,76.7–99.9%) and specificity of 89.7% (95% CI, 60.4–96.6%) after leave-one-out cross validation, regardless of HIV infection status. Eight-marker biosignatures performed with a sensitivity of 100% (95% CI, 83.2–100%) and specificity of 95% (95% CI, 68.1–99.9%) in the absence of HIV infection. Furthermore, the concentrations of 11 of the markers changed during treatment, indicating that they may be useful in monitoring of TB treatment response. Conclusion: We have identified novel salivary biosignatures which may be useful in the diagnosis of TB disease and monitoring of the response to TB treatment. Our findings require further validation in larger studies before these biosignatures could be considered for point-of-care screening test development.
- ItemDistinct serum biosignatures are associated with different tuberculosis treatment outcomes(Elsevier, 2019) Ronachera, Katharina; Chegoua, Novel N.; Kleynhansa, Leanie; Siawayac, Joel F. Djoba; Du Plessis, Nelita; Loxton, Andre G.; Maasdorp, Elizna; Tromp, Gerard; Kidd, Martin; Stanleya, Kim; Kriela, Magdalena; Menezesa, Angela; Gutschmidta, Andrea; Van Der Spuya, Gian D.; Warrena, Robin M.; Dietzee, Reynaldo; Okweraf, Alphonse; Thielg, Bonnie; Belisleh, John T.; Cliffi, Jacqueline M.; Boomg, W. Henry; Johnsong, John L.; Van Heldena, Paul D.; Dockrelli, Hazel M.; Walzla, GerhardENGLISH ABSTRACT: Biomarkers for TB treatment response and outcome are needed. This study characterize changes in immune profiles during TB treatment, define biosignatures associated with treatment outcomes, and explore the feasibility of predictive models for relapse. Seventy-two markers were measured by multiplex cytokine array in serum samples from 78 cured, 12 relapsed and 15 failed treatment patients from South Africa before and during therapy for pulmonary TB. Promising biosignatures were evaluated in a second cohort from Uganda/Brazil consisting of 17 relapse and 23 cured patients. Thirty markers changed significantly with different response patterns during TB treatment in cured patients. The serum biosignature distinguished cured from relapse patients and a combination of two clinical (time to positivity in liquid culture and BMI) and four immunological parameters (TNF-β, sIL-6R, IL-12p40 and IP-10) at diagnosis predicted relapse with a 75% sensitivity (95%CI 0.38–1) and 85% specificity (95%CI 0.75–0.93). This biosignature was validated in an independent Uganda/Brazil cohort correctly classifying relapse patients with 83% (95%CI 0.58–1) sensitivity and 61% (95%CI 0.39–0.83) specificity. A characteristic biosignature with value as predictor of TB relapse was identified. The repeatability and robustness of these biomarkers require further validation in well-characterized cohorts.
- ItemThe functional response of B cells to antigenic stimulation : a preliminary report of latent tuberculosis(Public Library of Science, 2016-04) Du Plessis, Willem J.; Kleynhans, Leanie; Du Plessis, Nelita; Stanley, Kim; Malherbe, Stephanus T.; Maasdorp, Elizna; Ronacher, Katharina; Chegou, Novel N.; Walzl, Gerhard; Loxton, Andre G.Mycobacterium tuberculosis (M.tb) remains a successful pathogen, causing tuberculosis disease numbers to constantly increase. Although great progress has been made in delineating the disease, the host-pathogen interaction is incompletely described. B cells have shown to function as both effectors and regulators of immunity via non-humoral methods in both innate and adaptive immune settings. Here we assessed specific B cell functional interaction following stimulation with a broad range of antigens within the LTBI milieu. Our results indicate that B cells readily produce pro- and anti-inflammatory cytokines (including IL-1β, IL-10, IL-17, IL-21 and TNF-α) in response to stimulation. TLR4 and TLR9 based stimulations achieved the greatest secreted cytokine-production response and BCG stimulation displayed a clear preference for inducing IL-1β production. We also show that the cytokines produced by B cells are implicated strongly in cell-mediated communication and that plasma (memory) B cells (CD19+CD27+CD138+) is the subset with the greatest contribution to cytokine production. Collectively our data provides insight into B cell responses, where they are implicated in and quantifies responses from specific B cell phenotypes. These findings warrant further functional B cell research with a focus on specific B cell phenotypes under conditions of active TB disease to further our knowledge about the contribution of various cell subsets which could have implications for future vaccine development or refined B cell orientated treatment in the health setting.
- ItemQuantitative 18F-FDG PET-CT scan characteristics correlate with tuberculosis treatment response(SpringerOpen (part of Springer Nature), 2020-02-10) Malherbe, Stephanus T.; Chen, Ray Y.; Dupont, Patrick; Kant, Ilse; Kriel, Magdalena; Loxton, Andre G.; Smith, Bronwyn; Beltran, Caroline G. G.; Van Zyl, Susan; McAnda, Shirely; Abrahams, Charmaine; Maasdorp, Elizna; Doruyter, Alex; Via, Laura E.; Barry, Clifton E.; Alland, David; Richards, Stephanie G.; Ellman, Annare; Peppard, Thomas; Belisle, John; Tromp, Gerard; Ronacher, Katharina; Warwick, James M.; Winter, Jill; Walzl, GerhardBackground: There is a growing interest in the use of F-18 FDG PET-CT to monitor tuberculosis (TB) treatment response. Tuberculosis lung lesions are often complex and diffuse, with dynamic changes during treatment and persisting metabolic activity after apparent clinical cure. This poses a challenge in quantifying scan-based markers of burden of disease and disease activity. We used semi-automated, whole lung quantification of lung lesions to analyse serial FDG PET-CT scans from the Catalysis TB Treatment Response Cohort to identify characteristics that best correlated with clinical and microbiological outcomes. Results: Quantified scan metrics were already associated with clinical outcomes at diagnosis and 1 month after treatment, with further improved accuracy to differentiate clinical outcomes after standard treatment duration (month 6). A high cavity volume showed the strongest association with a risk of treatment failure (AUC 0.81 to predict failure at diagnosis), while a suboptimal reduction of the total glycolytic activity in lung lesions during treatment had the strongest association with recurrent disease (AUC 0.8 to predict pooled unfavourable outcomes). During the first year after TB treatment lesion burden reduced; but for many patients, there were continued dynamic changes of individual lesions. Conclusions: Quantification of FDG PET-CT images better characterised TB treatment outcomes than qualitative scan patterns and robustly measured the burden of disease. In future, validated metrics may be used to stratify patients and help evaluate the effectiveness of TB treatment modalities.
- ItemQuantitative 18F-FDG PET-CT scan characteristics correlate with tuberculosis treatment response(SpringerOpen (part of Springer Nature), 2020) Malherbe, Stephanus T.; Chen, Ray Y.; Dupont, Patrick; Kant, Ilse; Kriel, Magdalena; Loxton, Andre G.; Smith, Bronwyn; Beltran, Caroline G. G.; Van Zyl, Susan; McAnda, Shirely; Abrahams, Charmaine; Maasdorp, Elizna; Doruyter, Alex; Via, Laura E.; Barry, Clifton E.; Alland, David; Griffith- Richards, Stephanie; Ellman, Annare; Peppard, Thomas; Belisle, John; Tromp, Gerard; Ronacher, Katharina; Warwick, James M.; Winter, Jill; Walzl, GerhardBackground: There is a growing interest in the use of F-18 FDG PET-CT to monitor tuberculosis (TB) treatment response. Tuberculosis lung lesions are often complex and diffuse, with dynamic changes during treatment and persisting metabolic activity after apparent clinical cure. This poses a challenge in quantifying scan-based markers of burden of disease and disease activity. We used semi-automated, whole lung quantification of lung lesions to analyse serial FDG PET-CT scans from the Catalysis TB Treatment Response Cohort to identify characteristics that best correlated with clinical and microbiological outcomes. Results: Quantified scan metrics were already associated with clinical outcomes at diagnosis and 1 month after treatment, with further improved accuracy to differentiate clinical outcomes after standard treatment duration (month 6). A high cavity volume showed the strongest association with a risk of treatment failure (AUC 0.81 to predict failure at diagnosis), while a suboptimal reduction of the total glycolytic activity in lung lesions during treatment had the strongest association with recurrent disease (AUC 0.8 to predict pooled unfavourable outcomes). During the first year after TB treatment lesion burden reduced; but for many patients, there were continued dynamic changes of individual lesions. Conclusions: Quantification of FDG PET-CT images better characterised TB treatment outcomes than qualitative scan patterns and robustly measured the burden of disease. In future, validated metrics may be used to stratify patients and help evaluate the effectiveness of TB treatment modalities.
- ItemTargeting of myeloid-derived suppressor cells by all-trans retinoic acid as host-directed therapy for human tuberculosis(Elsevier Inc., 2021-06) Leukes, Vinzeigh N.; Dorhoi, Anca; Malherbe, Stephanus T.; Maasdorp, Elizna; Khoury, Justine; McAnda, Shirley; Walzl, Gerhard; Du Plessis, NelitaConventional anti-tuberculosis (TB) therapies comprise lengthy antibiotic treatment regimens, exacerbated by multi-drug resistant and extensively drug resistant mycobacterial strains. We assessed the ability of all-trans retinoic acid (ATRA), as repurposed compound serving as host-directed therapy (HDT), to counteract the suppressive effects of myeloid-derived suppressor cells (MDSCs) obtained from active TB cases (untreated or during week one of treatment) on T-cell responsiveness. We show for the first time that MDSCs suppress non-specific T-cell activation and production of interleukin (IL)-2, IL-4, IL-13 and GM-CSF via contact-dependent mechanisms. ATRA treatment decreases MDSC frequency, but fails to mature MDSCs to non-suppressive, terminally differentiated myeloid cells and does not restore T-cell function or cytokine production in the presence of MDSCs. The impact of ATRA treatment on improved immunity, using the concentration tested here, is likely to be minimal, but further identification and development of MDSC-targeting TB host-directed therapies are warranted.
- ItemTransition from restrictive to obstructive lung function impairment during treatment and follow-up of active tuberculosis(Dove Medical Press, 2020) Allwood, Brian W.; Maasdorp, Elizna; Kim, Grace J.; Cooper, Christopher B.; Goldin, Jonathan; Van Zyl-Smit, Richard N.; Bateman, Eric D.; Dawson, RodneyBackground: Pulmonary tuberculosis (PTB) is associated with many forms of chronic lung disease including the development of chronic airflow obstruction (AFO). However, the nature, evolution and mechanisms responsible for the AFO after PTB are poorly understood. The aim of this study was to examine the progression of changes in lung physiology in patients treated for PTB. Methods: Immunocompetent, previously healthy, adult patients receiving ambulatory treatment for a first episode of tuberculosis were prospectively followed up with serial lung physiology and quantitative computed tomography (CT) lung scans performed at diagnosis of tuberculosis, 2, 6, 12 and 18 months during and after the completion of treatment. Results: Forty-nine patients (median age 26 years; 37.2% males) were included, and 43 were studied. During treatment, lung volumes improved and CT fibrosis scores decreased, but features of AFO and gas trapping emerged, while reduced diffusing capacity (DLco) seen in a majority of patients persisted. Significant increases in total lung capacity (TLC) by plethysmography were seen in the year following treatment completion (median change 5.9% pred., P< 0.01) and were driven by large increases in residual volume (RV) (median change +19%pred., P< 0.01) but not inspiratory capacity (IC; P=0.41). The change in RV/TLC correlated with significant progression of radiological gas trapping after treatment (P=0.04) but not with emphysema scores. One year after completing treatment, 18.6% of patients had residual restriction (total lung capacity, TLC < 80%pred), 16.3% had AFO, 32.6% had gas trapping (RV/TLC> 45%), and 78.6% had reduced DLco. Conclusion: Simple spirometry alone does not fully reveal the residual respiratory impairments resulting after a first episode of PTB. Changes in physiology evolve after treatment completion, and these findings when taken together, suggest emergence of gas trapping after treatment likely caused by progression of small airway pathology during the healing process.
- ItemTransition from restrictive to obstructive lung function impairment during treatment and follow-up of active tuberculosis(Dove Press, 2020-05) Allwood, Brian W.; Maasdorp, Elizna; Kim, Grace J.; Cooper, Christopher B.; Goldin, Jonathan; van Zyl-Smit, Richard N.; Bateman, Eric D.; Dawson, RodneyBackground: Pulmonary tuberculosis (PTB) is associated with many forms of chronic lung disease including the development of chronic airflow obstruction (AFO). However, the nature, evolution and mechanisms responsible for the AFO after PTB are poorly understood. The aim of this study was to examine the progression of changes in lung physiology in patients treated for PTB. Methods: Immunocompetent, previously healthy, adult patients receiving ambulatory treatment for a first episode of tuberculosis were prospectively followed up with serial lung physiology and quantitative computed tomography (CT) lung scans performed at diagnosis of tuberculosis, 2, 6, 12 and 18 months during and after the completion of treatment. Results: Forty-nine patients (median age 26 years; 37.2% males) were included, and 43 were studied. During treatment, lung volumes improved and CT fibrosis scores decreased, but features of AFO and gas trapping emerged, while reduced diffusing capacity (DLco) seen in a majority of patients persisted. Significant increases in total lung capacity (TLC) by plethysmography were seen in the year following treatment completion (median change 5.9% pred., P<0.01) and were driven by large increases in residual volume (RV) (median change +19%pred., P<0.01) but not inspiratory capacity (IC; P=0.41). The change in RV/TLC correlated with significant progression of radiological gas trapping after treatment (P=0.04) but not with emphysema scores. One year after completing treatment, 18.6% of patients had residual restriction (total lung capacity, TLC <80%pred), 16.3% had AFO, 32.6% had gas trapping (RV/TLC>45%), and 78.6% had reduced DLco. Conclusion: Simple spirometry alone does not fully reveal the residual respiratory impairments resulting after a first episode of PTB. Changes in physiology evolve after treatment completion, and these findings when taken together, suggest emergence of gas trapping after treatment likely caused by progression of small airway pathology during the healing process. Keywords: airflow obstruction; chronic obstructive pulmonary disease; computed tomography; lung function; post-tuberculosis; tuberculosis.