Browsing by Author "Esterhuyse, Maria M."

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    Africa-wide evaluation of host biomarkers in QuantiFERON supernatants for the diagnosis of pulmonary tuberculosis
    (Nature Research, 2018-02-08) Chegou, Novel N.; Sutherland, Jayne S.; Namuganga, Anna-Ritah; Corstjens, Paul L. A. M.; Geluk, Annemieke; Gebremichael, Gebremedhin; Mendy, Joseph; Malherbe, Stephanus; Stanley, Kim; Van Der Spuy, Gian D.; Kriel, Magdalena; Loxton, Andre G.; Kriel, Belinda; Simukonda, Felanji; Bekele, Yonas; Sheehama, Jacob A.; Nelongo, Josefina; Van Der Vyver, Marieta; Gebrexabher, Atsbeha; Hailu, Habteyes; Esterhuyse, Maria M.; Rosenkrands, Ida; Aagard, Claus; Kidd, Martin; Kassa, Desta; Mihret, Adane; Howe, Rawleigh; Cliff, Jacqueline M.; Crampin, Amelia C.; Mayanja-Kizza, Harriet; Kaufmann, Stefan H. E.; Dockrell, Hazel M.; Ottenhoff, Tom H. M.; Walzl, Gerhard; AE-TBC consortium
    We investigated host-derived biomarkers that were previously identified in QuantiFERON supernatants, in a large pan-African study. We recruited individuals presenting with symptoms of pulmonary TB at seven peripheral healthcare facilities in six African countries, prior to assessment for TB disease. We then evaluated the concentrations of 12 biomarkers in stored QuantiFERON supernatants using the Luminex platform. Based on laboratory, clinical and radiological findings and a pre-established algorithm, participants were classified as TB disease or other respiratory diseases(ORD). Of the 514 individuals included in the study, 179(34.8%) had TB disease, 274(51.5%) had ORD and 61(11.5%) had an uncertain diagnosis. A biosignature comprising unstimulated IFN-γ, MIP-1β, TGF-α and antigen-specific levels of TGF-α and VEGF, identified on a training sample set (n = 311), validated by diagnosing TB disease in the test set (n = 134) with an AUC of 0.81(95% CI, 0.76–0.86), corresponding to a sensitivity of 64.2%(95% CI, 49.7–76.5%) and specificity of 82.7%(95% CI, 72.4–89.9%). Host biomarkers detected in QuantiFERON supernatants can contribute to the diagnosis of active TB disease amongst people presenting with symptoms requiring investigation for TB disease, regardless of HIV status or ethnicity in Africa.
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    Epigenetics and proteomics join transcriptomics in the quest for tuberculosis biomarkers
    (American Society for Microbiology, 2015-09-15) Esterhuyse, Maria M.; Weiner, January; Caron, Etienne; Loxton, Andre G.; Iannaccone, Marco; Wagman, Chandre; Saikali, Philippe; Stanley, Kim; Wolski, Witold E.; Mollenkopf, Hans-Joachim; Schick, Matthias; Aebersold, Ruedi; Linhart, Heinz; Walzl, Gerhard; Kaufmann, Stefan H. E.
    An estimated one-third of the world’s population is currently latently infected with Mycobacterium tuberculosis. Latent M. tuberculosis infection (LTBI) progresses into active tuberculosis (TB) disease in ~5 to 10% of infected individuals. Diagnostic and prognostic biomarkers to monitor disease progression are urgently needed to ensure better care for TB patients and to decrease the spread of TB. Biomarker development is primarily based on transcriptomics. Our understanding of biology combined with evolving technical advances in high-throughput techniques led us to investigate the possibility of additional platforms (epigenetics and proteomics) in the quest to (i) understand the biology of the TB host response and (ii) search for multiplatform biosignatures in TB. We engaged in a pilot study to interrogate the DNA methylome, transcriptome, and proteome in selected monocytes and granulocytes from TB patients and healthy LTBI participants. Our study provides first insights into the levels and sources of diversity in the epigenome and proteome among TB patients and LTBI controls, despite limitations due to small sample size. Functionally the differences between the infection phenotypes (LTBI versus active TB) observed in the different platforms were congruent, thereby suggesting regulation of function not only at the transcriptional level but also by DNA methylation and microRNA. Thus, our data argue for the development of a large-scale study of the DNA methylome, with particular attention to study design in accounting for variation based on gender, age, and cell type.