Multivariate analysis of the immune response upon recent acquisition of Mycobacterium tuberculosis infection

Tuberculosis (TB), caused by the pathogen Mycobacterium tuberculosis (M.tb), is the leading cause of mortality due to an infectious agent worldwide. Based on data from an adolescent cohort study carried out from May 2005 to February 2009, we studied and compared the immune responses of individuals from four cohorts that were defined based on their longitudinal QFT results: the recent QFT converters, the QFT reverters, the persistent QFT positives and negatives. Analysis was based on the integration of different arms of the immune response, including adaptive and “innaptive” responses, measured on the cohorts. COMPASS was used to filter the adaptive dataset and identify bioligically meaningful subsets, while, for the innaptive dataset, we came up with a novel filtering method. Once the datasets were integrated, they were standardized using variance stabilizing (vast) standardization and missing values were imputed using a multiple factor analysis (MFA)-based approach. We first set out to define a set of immune features that changed during recent M.tb infection. This was achieved by employing the kmlShape clustering algorithm to the recent QFT converters. We identified 55 cell subsets to either increase or decrease post-infection. When we assessed how the associations between these changed pre- and post-infection using correlation networks, we found no notable differences. By comparing the recent QFT converters and the persistent QFT positives, a blood-based biomarker to distinguish between recent and established infection, namely ESAT6/CFP10-specific expression of HLA-DR on total Th1 cells, was identified using elastic net (EN) models (average AUROC = 0.87). The discriminatory ability of this variable was confirmed using two tree-based models. Lastly, to assess whether the QFT reverters are a biologically distinct group of individuals, we compared them to the persistent QFT positive and QFT negative individuals using a Projection to Latent Space Discriminant Analysis (PLS-DA) model. The results indicated that reverters appeared more similar to QFT negative individuals rather than QFT positive. Hence, QFT reversion may be associated with clearance of M.tb infection. Immune signatures associated with recent infection could be used to refine end-points of clinical trials testing vaccine efficacy against acquisition of M.tb infection, while immune signatures associated with QFT reversion could be tested as correlates of protection from M.tb infection.

Grantor

Department of Statistical Sciences

Year dc:date.issued

2021

Author dc:creator

• Lloyd, Tessa

Advisors dc:contributor.advisor

• Little, Francesca
• Nemes, Elisa
• Steigler, Pia

• Statistical Sciences

Handle dc:identifier.uri

http://hdl.handle.net/11427/35909

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/35909