Multidimensional analysis of immune responses identified biomarkers of recent < i > Mycobacterium tuberculosis < /i > infection

by Tessa Lloyd, Pia Steigler, Cheleka A. M. Mpande, Virginie Rozot, Boitumelo Mosito, Constance Schreuder, Timothy D. Reid, Mark Hatherill, Thomas J. Scriba, Francesca Little, Elisa Nemes, the ACS Study Team The risk of tuberculosis (TB) disease is higher in individuals with recentMycobacterium tuberculosis (M.tb) infection compared to individuals with more remote, established infection. We aimed to define blood-based biomarkers to distinguish between recent and remote infection, which would allow targeting of recently infected individuals for preventive TB treatment. We hypothesized that integration of multiple immune measurements would outperform the diagnostic performance of a single biomarker. Analysis was performed on different components of the immune system, including adaptive and innate responses to mycobacteria, measured on recently and remotelyM.tb infected adolescents. The datasets were standardized using variance stabilizing scaling and missing values were imputed using a multiple factor analysis-based approach. For data integration, we compared the performance of a Multiple Tuning Parameter Elastic Net (MTP-EN) to a standard EN model, which was built to the individual adaptive and innate datasets. Biomarkers with non-zero coefficients from the optimal single data EN models were then isolated to build logistic regression models. A decision tree and random forest model were used for statistical confirmation. We found no difference in the predictive performances of...
Source: PLoS Computational Biology - Category: Biology Authors: Source Type: research